llama-1B/64_GPUS/dp-1_tp-16_pp-4_mbz-32/log.out

========================
START TIME: Sat Jul  6 09:23:47 UTC 2024
python3 version = Python 3.10.14
========================
The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.
Token is valid (permission: write).
Your token has been saved to /admin/home/ferdinand_mom/.cache/huggingface/token
Login successful
Already on 'bench_cluster'
M	examples/config_tiny_llama.py
M	examples/config_tiny_llama.yaml
M	examples/train_tiny_llama.sh
Your branch is up to date with 'origin/bench_cluster'.
Job status: RUNNING
[2024-07-06 09:23:49,722] torch.distributed.run: [WARNING] 
[2024-07-06 09:23:49,722] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,722] 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 09:23:49,722] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,735] torch.distributed.run: [WARNING] 
[2024-07-06 09:23:49,735] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,735] 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 09:23:49,735] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,778] torch.distributed.run: [WARNING] 
[2024-07-06 09:23:49,778] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,778] 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 09:23:49,778] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,788] torch.distributed.run: [WARNING] 
[2024-07-06 09:23:49,788] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,788] 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 09:23:49,788] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,788] torch.distributed.run: [WARNING] 
[2024-07-06 09:23:49,788] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,788] 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 09:23:49,788] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,790] torch.distributed.run: [WARNING] 
[2024-07-06 09:23:49,790] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,790] 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 09:23:49,790] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,812] torch.distributed.run: [WARNING] 
[2024-07-06 09:23:49,812] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,812] 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 09:23:49,812] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,884] torch.distributed.run: [WARNING] 
[2024-07-06 09:23:49,884] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:23:49,884] 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 09:23:49,884] torch.distributed.run: [WARNING] *****************************************
[default0]:07/06/2024 09:24:07 [WARNING|DP=0|PP=0|TP=0|ip-26-0-168-120]: [Vocab Size Padding] Padded vocab (size: 50257) with 15 dummy tokens (new size: 50272)
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: Config:
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: Config(general=GeneralArgs(project='bench_cluster',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                            run='%date_%jobid',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                            seed=42,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                            step=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                            consumed_train_samples=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                            benchmark_csv_path=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                            ignore_sanity_checks=True),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:        parallelism=ParallelismArgs(dp=1,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                    pp=4,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                    tp=16,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                    pp_engine=<nanotron.parallel.pipeline_parallel.engine.AllForwardAllBackwardPipelineEngine object at 0x7f064f0e0730>,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                    tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                    tp_linear_async_communication=False,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                    expert_parallel_size=1),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:        model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 eos_token_id=2,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 hidden_act='silu',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 hidden_size=2048,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 initializer_range=0.02,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 intermediate_size=4096,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 is_llama_config=True,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 max_position_embeddings=4096,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 num_attention_heads=32,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 num_hidden_layers=24,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 num_key_value_heads=32,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 pad_token_id=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 pretraining_tp=1,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 rms_norm_eps=1e-05,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 rope_scaling=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 rope_theta=10000.0,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 tie_word_embeddings=True,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 use_cache=True,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                 vocab_size=50272),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                        init_method=RandomInit(std=0.025),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                        dtype=torch.bfloat16,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                        make_vocab_size_divisible_by=1,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                        ddp_bucket_cap_mb=25),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:        tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                tokenizer_revision=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                tokenizer_max_length=None),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:        checkpoints=CheckpointsArgs(checkpoints_path=PosixPath('/dev/null'),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                    checkpoint_interval=100000,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                    save_initial_state=False,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                    resume_checkpoint_path=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                    checkpoints_path_is_shared_file_system=False),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:        logging=LoggingArgs(log_level='info',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                            log_level_replica='info',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                            iteration_step_info_interval=1),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:        tokens=TokensArgs(sequence_length=4096,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                          train_steps=20,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                          micro_batch_size=32,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                          batch_accumulation_per_replica=32,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                          val_check_interval=-1,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                          limit_val_batches=0,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                          limit_test_batches=0),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:        optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                     adam_beta1=0.9,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                     adam_beta2=0.95,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                     torch_adam_is_fused=True,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                     name='adamW'),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                zero_stage=1,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                weight_decay=0.01,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                clip_grad=1.0,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                accumulate_grad_in_fp32=True,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                        lr_warmup_steps=1,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                        lr_warmup_style='linear',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                        lr_decay_style='linear',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                        lr_decay_steps=19,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                        lr_decay_starting_step=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                        min_decay_lr=1e-05)),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:        data_stages=[DatasetStageArgs(name='Training Stage',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                      start_training_step=1,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                      data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                                 hf_dataset_splits='train',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                                 hf_dataset_config_name=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                                 dataset_processing_num_proc_per_process=64,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                                 dataset_overwrite_cache=False,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                                                 text_column_name='text'),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                    seed=42,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:                                                    num_loading_workers=0))],
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:        profiler=ProfilerArgs(profiler_export_path=PosixPath('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/64_GPUS/dp-1_tp-16_pp-4_mbz-32')),
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:        lighteval=None)
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: Model Config:
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: LlamaConfig(bos_token_id=1,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             eos_token_id=2,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             hidden_act='silu',
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             hidden_size=2048,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             initializer_range=0.02,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             intermediate_size=4096,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             is_llama_config=True,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             max_position_embeddings=4096,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             num_attention_heads=32,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             num_hidden_layers=24,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             num_key_value_heads=32,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             pad_token_id=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             pretraining_tp=1,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             rms_norm_eps=1e-05,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             rope_scaling=None,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             rope_theta=10000.0,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             tie_word_embeddings=True,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             use_cache=True,
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:             vocab_size=50272)
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: Building model..
[default0]:07/06/2024 09:24:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: Setting PP block ranks...
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=5|ip-26-0-169-207]: Local number of parameters: 15.8M (30.05MiB)
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=5|ip-26-0-169-207]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=5|ip-26-0-169-207]: No checkpoint path provided.
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=3|ip-26-0-169-207]: Local number of parameters: 15.8M (30.05MiB)
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=3|ip-26-0-169-207]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=3|ip-26-0-169-207]: No checkpoint path provided.
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=2|ip-26-0-169-207]: Local number of parameters: 15.8M (30.05MiB)
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=2|ip-26-0-169-207]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=2|ip-26-0-169-207]: No checkpoint path provided.
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=1|ip-26-0-169-207]: Local number of parameters: 15.8M (30.05MiB)
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=1|ip-26-0-169-207]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=1|ip-26-0-169-207]: No checkpoint path provided.
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=6|ip-26-0-168-120]: Local number of parameters: 24.8M (47.33MiB)
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=6|ip-26-0-168-120]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=1|ip-26-0-168-120]: Local number of parameters: 24.8M (47.33MiB)
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=1|ip-26-0-168-120]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=6|ip-26-0-168-120]: No checkpoint path provided.
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=2|ip-26-0-168-120]: Local number of parameters: 24.8M (47.33MiB)
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=2|ip-26-0-168-120]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=2|ip-26-0-168-120]: No checkpoint path provided.
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=3|ip-26-0-168-120]: Local number of parameters: 24.8M (47.33MiB)
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=3|ip-26-0-168-120]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=5|ip-26-0-168-120]: Local number of parameters: 24.8M (47.33MiB)
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=1|ip-26-0-168-120]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: Total number of parameters: 1.21G (2315.81MiB)
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=3|ip-26-0-168-120]: No checkpoint path provided.
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=5|ip-26-0-168-120]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=5|ip-26-0-168-120]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: Local number of parameters: 24.8M (47.33MiB)
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: Parametrizing model parameters using StandardParametrizator
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=7|ip-26-0-168-120]: Local number of parameters: 24.8M (47.33MiB)
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=7|ip-26-0-168-120]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=7|ip-26-0-168-120]: No checkpoint path provided.
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=6|ip-26-0-169-207]: Local number of parameters: 15.8M (30.05MiB)
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=6|ip-26-0-169-207]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=6|ip-26-0-169-207]: No checkpoint path provided.
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=4|ip-26-0-168-120]: Local number of parameters: 24.8M (47.33MiB)
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=4|ip-26-0-168-120]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=4|ip-26-0-168-120]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-168]: Local number of parameters: 16.9M (32.31MiB)
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-168]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-168]: No checkpoint path provided.
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=1|ip-26-0-169-132]: Local number of parameters: 18.4M (35.05MiB)
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=1|ip-26-0-169-132]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=1|ip-26-0-169-132]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=0|ip-26-0-169-207]: Local number of parameters: 15.8M (30.05MiB)
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=0|ip-26-0-169-207]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=0|ip-26-0-169-207]: No checkpoint path provided.
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=10|ip-26-0-171-230]: Local number of parameters: 16.9M (32.31MiB)
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=10|ip-26-0-171-230]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=10|ip-26-0-171-230]: No checkpoint path provided.
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=13|ip-26-0-171-230]: Local number of parameters: 16.9M (32.31MiB)
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=13|ip-26-0-171-230]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=13|ip-26-0-171-230]: No checkpoint path provided.
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=12|ip-26-0-171-230]: Local number of parameters: 16.9M (32.31MiB)
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=12|ip-26-0-171-230]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=12|ip-26-0-171-230]: No checkpoint path provided.
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=11|ip-26-0-171-230]: Local number of parameters: 16.9M (32.31MiB)
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=11|ip-26-0-171-230]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=11|ip-26-0-171-230]: No checkpoint path provided.
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=1|ip-26-0-171-168]: Local number of parameters: 16.9M (32.31MiB)
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=1|ip-26-0-171-168]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=1|ip-26-0-171-168]: No checkpoint path provided.
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=7|ip-26-0-171-168]: Local number of parameters: 16.9M (32.31MiB)
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=7|ip-26-0-171-168]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=7|ip-26-0-171-168]: No checkpoint path provided.
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=3|ip-26-0-171-168]: Local number of parameters: 16.9M (32.31MiB)
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=3|ip-26-0-171-168]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=3|ip-26-0-171-168]: No checkpoint path provided.
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=9|ip-26-0-171-230]: Local number of parameters: 16.9M (32.31MiB)
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=9|ip-26-0-171-230]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=9|ip-26-0-171-230]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=8|ip-26-0-171-230]: Local number of parameters: 16.9M (32.31MiB)
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=5|ip-26-0-169-132]: Local number of parameters: 18.4M (35.05MiB)
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=5|ip-26-0-169-132]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=5|ip-26-0-169-132]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=8|ip-26-0-171-230]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=15|ip-26-0-171-230]: Local number of parameters: 16.9M (32.31MiB)
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=15|ip-26-0-171-230]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=14|ip-26-0-171-230]: Local number of parameters: 16.9M (32.31MiB)
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=14|ip-26-0-171-230]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=3|ip-26-0-169-132]: Local number of parameters: 18.4M (35.05MiB)
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=3|ip-26-0-169-132]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=3|ip-26-0-169-132]: No checkpoint path provided.
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=14|ip-26-0-171-230]: No checkpoint path provided.
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=15|ip-26-0-171-230]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=8|ip-26-0-171-230]: No checkpoint path provided.
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=5|ip-26-0-171-168]: Local number of parameters: 16.9M (32.31MiB)
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=5|ip-26-0-171-168]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=5|ip-26-0-171-168]: No checkpoint path provided.
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=4|ip-26-0-169-132]: Local number of parameters: 18.4M (35.05MiB)
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=4|ip-26-0-171-168]: Local number of parameters: 16.9M (32.31MiB)
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=4|ip-26-0-171-168]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=4|ip-26-0-171-168]: No checkpoint path provided.
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=4|ip-26-0-169-132]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=4|ip-26-0-169-132]: No checkpoint path provided.
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=7|ip-26-0-169-207]: Local number of parameters: 15.8M (30.05MiB)
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-132]: Local number of parameters: 18.4M (35.05MiB)
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-132]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-132]: No checkpoint path provided.
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=7|ip-26-0-169-207]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=7|ip-26-0-169-207]: No checkpoint path provided.
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=4|ip-26-0-169-207]: Local number of parameters: 15.8M (30.05MiB)
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=4|ip-26-0-169-207]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=4|ip-26-0-169-207]: No checkpoint path provided.
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=2|ip-26-0-169-132]: Local number of parameters: 18.4M (35.05MiB)
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=2|ip-26-0-169-132]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=2|ip-26-0-169-132]: No checkpoint path provided.
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=2|ip-26-0-171-168]: Local number of parameters: 16.9M (32.31MiB)
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=2|ip-26-0-171-168]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=2|ip-26-0-171-168]: No checkpoint path provided.
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=6|ip-26-0-171-168]: Local number of parameters: 16.9M (32.31MiB)
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=6|ip-26-0-171-168]: [After model building] Memory usage: 36.32MiB. Peak allocated: 38.35MiB Peak reserved: 48.00MiB
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=3|TP=6|ip-26-0-171-168]: No checkpoint path provided.
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=6|ip-26-0-169-132]: Local number of parameters: 18.4M (35.05MiB)
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=6|ip-26-0-169-132]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=6|ip-26-0-169-132]: No checkpoint path provided.
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=7|ip-26-0-169-132]: Local number of parameters: 18.4M (35.05MiB)
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=7|ip-26-0-169-132]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=7|ip-26-0-169-132]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=8|ip-26-0-169-86]: Local number of parameters: 15.8M (30.05MiB)
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=8|ip-26-0-169-86]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=8|ip-26-0-169-86]: No checkpoint path provided.
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=10|ip-26-0-169-86]: Local number of parameters: 15.8M (30.05MiB)
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=10|ip-26-0-169-86]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=10|ip-26-0-169-86]: No checkpoint path provided.
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=14|ip-26-0-169-86]: Local number of parameters: 15.8M (30.05MiB)
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=14|ip-26-0-169-86]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=14|ip-26-0-169-86]: No checkpoint path provided.
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=11|ip-26-0-169-86]: Local number of parameters: 15.8M (30.05MiB)
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=11|ip-26-0-169-86]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=11|ip-26-0-169-86]: No checkpoint path provided.
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=9|ip-26-0-169-86]: Local number of parameters: 15.8M (30.05MiB)
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=9|ip-26-0-169-86]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=9|ip-26-0-169-86]: No checkpoint path provided.
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=9|ip-26-0-169-139]: Local number of parameters: 18.4M (35.05MiB)
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=9|ip-26-0-169-139]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=9|ip-26-0-169-139]: No checkpoint path provided.
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=11|ip-26-0-169-139]: Local number of parameters: 18.4M (35.05MiB)
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=11|ip-26-0-169-139]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=11|ip-26-0-169-139]: No checkpoint path provided.
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=15|ip-26-0-169-139]: Local number of parameters: 18.4M (35.05MiB)
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=15|ip-26-0-169-139]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=15|ip-26-0-169-139]: No checkpoint path provided.
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=12|ip-26-0-169-86]: Local number of parameters: 15.8M (30.05MiB)
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=13|ip-26-0-169-139]: Local number of parameters: 18.4M (35.05MiB)
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=12|ip-26-0-169-86]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=12|ip-26-0-169-86]: No checkpoint path provided.
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=13|ip-26-0-169-139]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=13|ip-26-0-169-139]: No checkpoint path provided.
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=15|ip-26-0-169-86]: Local number of parameters: 15.8M (30.05MiB)
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=15|ip-26-0-169-86]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=8|ip-26-0-169-139]: Local number of parameters: 18.4M (35.05MiB)
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=15|ip-26-0-169-86]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=8|ip-26-0-169-139]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=8|ip-26-0-169-139]: No checkpoint path provided.
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=13|ip-26-0-169-86]: Local number of parameters: 15.8M (30.05MiB)
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=13|ip-26-0-169-86]: [After model building] Memory usage: 37.06MiB. Peak allocated: 39.09MiB Peak reserved: 58.00MiB
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=2|TP=13|ip-26-0-169-86]: No checkpoint path provided.
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=14|ip-26-0-169-139]: Local number of parameters: 18.4M (35.05MiB)
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=14|ip-26-0-169-139]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=14|ip-26-0-169-139]: No checkpoint path provided.
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=10|ip-26-0-169-139]: Local number of parameters: 18.4M (35.05MiB)
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=10|ip-26-0-169-139]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=10|ip-26-0-169-139]: No checkpoint path provided.
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=12|ip-26-0-169-139]: Local number of parameters: 18.4M (35.05MiB)
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=12|ip-26-0-169-139]: [After model building] Memory usage: 43.07MiB. Peak allocated: 45.10MiB Peak reserved: 60.00MiB
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=1|TP=12|ip-26-0-169-139]: No checkpoint path provided.
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=8|ip-26-0-168-238]: Local number of parameters: 24.8M (47.33MiB)
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=8|ip-26-0-168-238]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default0]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=8|ip-26-0-168-238]: No checkpoint path provided.
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=12|ip-26-0-168-238]: Local number of parameters: 24.8M (47.33MiB)
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=12|ip-26-0-168-238]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default4]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=12|ip-26-0-168-238]: No checkpoint path provided.
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=14|ip-26-0-168-238]: Local number of parameters: 24.8M (47.33MiB)
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=14|ip-26-0-168-238]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default6]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=14|ip-26-0-168-238]: No checkpoint path provided.
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=9|ip-26-0-168-238]: Local number of parameters: 24.8M (47.33MiB)
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=9|ip-26-0-168-238]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default1]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=9|ip-26-0-168-238]: No checkpoint path provided.
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=13|ip-26-0-168-238]: Local number of parameters: 24.8M (47.33MiB)
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=13|ip-26-0-168-238]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default5]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=13|ip-26-0-168-238]: No checkpoint path provided.
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=10|ip-26-0-168-238]: Local number of parameters: 24.8M (47.33MiB)
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=10|ip-26-0-168-238]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default2]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=10|ip-26-0-168-238]: No checkpoint path provided.
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=11|ip-26-0-168-238]: Local number of parameters: 24.8M (47.33MiB)
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=11|ip-26-0-168-238]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default3]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=11|ip-26-0-168-238]: No checkpoint path provided.
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=15|ip-26-0-168-238]: Local number of parameters: 24.8M (47.33MiB)
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=15|ip-26-0-168-238]: [After model building] Memory usage: 55.07MiB. Peak allocated: 57.10MiB Peak reserved: 74.00MiB
[default7]:07/06/2024 09:24:26 [INFO|DP=0|PP=0|TP=15|ip-26-0-168-238]: No checkpoint path provided.
[default0]:07/06/2024 09:24:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: [Optimizer Building] Using LearningRateForSP as learning rate
[default0]:07/06/2024 09:24:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: [ZeRO sharding] Size of optimizer params per rank:
[default0]:07/06/2024 09:24:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: [ZeRO sharding] DP Rank 0 has 24.8M out of 24.8M (100.00%) params' optimizer states
[default0]:07/06/2024 09:24:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
[default0]:07/06/2024 09:24:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: Using `datasets` library
[default0]:07/06/2024 09:24:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: 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 09:24:28 [WARNING|DP=0|PP=0|TP=0|ip-26-0-168-120]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:24:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: [Training Plan] There are 1 training stages 
[default0]:07/06/2024 09:24:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: [Stage Training Stage] start from step 1 
[default0]:07/06/2024 09:24:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: 
[default0]:07/06/2024 09:24:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: [Start training] datetime: 2024-07-06 09:24:29.399809 | mbs: 32 | grad_accum: 32 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
[default5]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=5|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=3|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=1|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=6|ip-26-0-168-120]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=3|ip-26-0-168-120]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=1|ip-26-0-168-120]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=5|ip-26-0-168-120]: Repo card metadata block was not found. Setting CardData to empty.
[default3]: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 09:24:29 [WARNING|DP=0|PP=0|TP=4|ip-26-0-168-120]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=0|ip-26-0-171-168]: 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 09:24:29 [WARNING|DP=0|PP=2|TP=0|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default1]: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.
[default3]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=11|ip-26-0-171-230]: 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 09:24:29 [WARNING|DP=0|PP=3|TP=1|ip-26-0-171-168]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=7|ip-26-0-171-168]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=5|ip-26-0-171-168]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=4|ip-26-0-171-168]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=5|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=3|ip-26-0-171-168]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=3|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=14|ip-26-0-171-230]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=15|ip-26-0-171-230]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=4|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=4|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=6|ip-26-0-171-168]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default3]: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 09:24:29 [WARNING|DP=0|PP=1|TP=7|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default4]: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 09:24:29 [WARNING|DP=0|PP=2|TP=9|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=10|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=11|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=9|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=13|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=8|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=12|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=15|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=14|ip-26-0-169-139]: 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.
[default4]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=12|ip-26-0-169-139]: 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 09:24:29 [WARNING|DP=0|PP=0|TP=8|ip-26-0-168-238]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=9|ip-26-0-168-238]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=13|ip-26-0-168-238]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=10|ip-26-0-168-238]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=11|ip-26-0-168-238]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default1]: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 09:24:29 [WARNING|DP=0|PP=2|TP=2|ip-26-0-169-207]: 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 09:24:29 [WARNING|DP=0|PP=0|TP=2|ip-26-0-168-120]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=6|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=13|ip-26-0-171-230]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=10|ip-26-0-171-230]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=9|ip-26-0-171-230]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=8|ip-26-0-171-230]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=7|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=2|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=6|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=8|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:24:29 [WARNING|DP=0|PP=2|TP=11|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=15|ip-26-0-169-139]: 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 09:24:29 [WARNING|DP=0|PP=2|TP=13|ip-26-0-169-86]: 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]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=12|ip-26-0-168-238]: 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 09:24:29 [WARNING|DP=0|PP=0|TP=15|ip-26-0-168-238]: 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.
[default4]:07/06/2024 09:24:29 [WARNING|DP=0|PP=3|TP=12|ip-26-0-171-230]: 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 09:24:29 [WARNING|DP=0|PP=2|TP=14|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=14|ip-26-0-168-238]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:24:29 [WARNING|DP=0|PP=0|TP=7|ip-26-0-168-120]: 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 09:24:29 [WARNING|DP=0|PP=3|TP=2|ip-26-0-171-168]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=0|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default7]: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 09:24:29 [WARNING|DP=0|PP=1|TP=10|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:24:29 [WARNING|DP=0|PP=1|TP=1|ip-26-0-169-132]: 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 09:24:55 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
[default0]:07/06/2024 09:24:55 [INFO|DP=0|PP=0|TP=0|ip-26-0-168-120]:  Memory usage: 244.38MiB. Peak allocated 244.38MiB. Peak reserved: 266.00MiB
[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 630, in forward
[default2]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[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 562, in forward
[default2]:    key_value_states = torch.cat([key_states.unsqueeze(0), value_states.unsqueeze(0)], dim=0)
[default2]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 64.00 MiB. GPU 2 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 69.99 GiB is allocated by PyTorch, and 53.09 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 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 597, in forward
[default3]:    output = self.o_proj(attention_output)
[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/tensor_parallel/nn.py", line 159, in forward
[default3]:    return row_linear(
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default3]:    out = F.linear(input, weight, bias)
[default3]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 3 has a total capacity of 79.33 GiB of which 21.94 MiB is free. Including non-PyTorch memory, this process has 79.29 GiB memory in use. Of the allocated memory 70.11 GiB is allocated by PyTorch, and 52.08 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 636, in forward
[default6]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_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/models/llama.py", line 171, in forward
[default6]:    hidden_states = self.down_proj(self.split_silu_mul(merged_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/tensor_parallel/nn.py", line 159, in forward
[default6]:    return row_linear(
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default6]:    out = F.linear(input, weight, bias)
[default6]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 6 has a total capacity of 79.33 GiB of which 499.94 MiB is free. Including non-PyTorch memory, this process has 78.83 GiB memory in use. Of the allocated memory 69.30 GiB is allocated by PyTorch, and 21.12 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 636, in forward
[default4]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_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/models/llama.py", line 171, in forward
[default4]:    hidden_states = self.down_proj(self.split_silu_mul(merged_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/tensor_parallel/nn.py", line 159, in forward
[default4]:    return row_linear(
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default4]:    out = F.linear(input, weight, bias)
[default4]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 4 has a total capacity of 79.33 GiB of which 499.94 MiB is free. Including non-PyTorch memory, this process has 78.83 GiB memory in use. Of the allocated memory 69.30 GiB is allocated by PyTorch, and 21.12 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 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
[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", 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 359, in forward
[default7]:    qkv_states = self.qkv_proj(
[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/tensor_parallel/nn.py", line 87, in forward
[default7]:    return column_linear(
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear
[default7]:    return F.linear(input, weight, bias)
[default7]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 7 has a total capacity of 79.33 GiB of which 27.94 MiB is free. Including non-PyTorch memory, this process has 79.29 GiB memory in use. Of the allocated memory 69.80 GiB is allocated by PyTorch, and 53.09 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]:Traceback (most recent call last):
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default6]:Traceback (most recent call last):
[default2]:Traceback (most recent call last):
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default3]:Traceback (most recent call last):
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default5]:    trainer.train(dataloader)
[default3]:    trainer.train(dataloader)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default6]:    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)
[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
[default3]:  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(
[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)
[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
[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
[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
[default5]:    return self._call_impl(*args, **kwargs)
[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
[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)
[default6]:    return self._call_impl(*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
[default6]:  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 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
[default6]:    return forward_call(*args, **kwargs)
[default5]:    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 764, in forward
[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)
[default6]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[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
[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 636, in forward
[default6]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_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/models/llama.py", line 171, in forward
[default6]:    hidden_states = self.down_proj(self.split_silu_mul(merged_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/tensor_parallel/nn.py", line 159, in forward
[default6]:    return row_linear(
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default6]:    out = F.linear(input, weight, bias)
[default6]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 6 has a total capacity of 79.33 GiB of which 499.94 MiB is free. Including non-PyTorch memory, this process has 78.83 GiB memory in use. Of the allocated memory 69.30 GiB is allocated by PyTorch, and 21.12 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 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
[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", 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 359, in forward
[default7]:    qkv_states = self.qkv_proj(
[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/tensor_parallel/nn.py", line 87, in forward
[default7]:    return column_linear(
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear
[default7]:    return F.linear(input, weight, bias)
[default7]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 96.00 MiB. GPU 7 has a total capacity of 79.33 GiB of which 27.94 MiB is free. Including non-PyTorch memory, this process has 79.29 GiB memory in use. Of the allocated memory 69.80 GiB is allocated by PyTorch, and 53.09 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 636, in forward
[default4]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_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/models/llama.py", line 171, in forward
[default4]:    hidden_states = self.down_proj(self.split_silu_mul(merged_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/tensor_parallel/nn.py", line 159, in forward
[default4]:    return row_linear(
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default4]:    out = F.linear(input, weight, bias)
[default4]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 4 has a total capacity of 79.33 GiB of which 499.94 MiB is free. Including non-PyTorch memory, this process has 78.83 GiB memory in use. Of the allocated memory 69.30 GiB is allocated by PyTorch, and 21.12 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]:STAGE:2024-07-06 09:25:30 74095:74095 ActivityProfilerController.cpp:314] Completed Stage: Warm Up
[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
[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
[default1]:    sharded_logits = self.model(
[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
[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
[default5]:    output = model(**micro_batch)
[default1]:    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 1511, in _wrapped_call_impl
[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
[default5]:    return self._call_impl(*args, **kwargs)
[default1]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default5]:    return forward_call(*args, **kwargs)
[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)
[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)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[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)
[default1]:    return forward_call(*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
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default5]:    return forward_call(*args, **kwargs)
[default1]:    output = self.pp_block(**new_kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[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
[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
[default1]:    return self._call_impl(*args, **kwargs)
[default5]:    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 630, in forward
[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 636, in forward
[default5]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_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
[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)
[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 171, in forward
[default5]:    hidden_states = self.down_proj(self.split_silu_mul(merged_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)
[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)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 597, in forward
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default1]:    output = self.o_proj(attention_output)
[default5]:    return row_linear(
[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
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[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
[default5]:    out = F.linear(input, weight, bias)
[default1]:    return forward_call(*args, **kwargs)
[default5]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 5 has a total capacity of 79.33 GiB of which 499.94 MiB is free. Including non-PyTorch memory, this process has 78.83 GiB memory in use. Of the allocated memory 69.30 GiB is allocated by PyTorch, and 21.12 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]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default1]:    return row_linear(
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default1]:    out = F.linear(input, weight, bias)
[default1]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 1 has a total capacity of 79.33 GiB of which 39.94 MiB is free. Including non-PyTorch memory, this process has 79.27 GiB memory in use. Of the allocated memory 70.11 GiB is allocated by PyTorch, and 52.08 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)
[default2]:    trainer.train(dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default0]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[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 597, in forward
[default0]:    output = self.o_proj(attention_output)
[default2]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[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
[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)
[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
[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)
[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
[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
[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
[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)
[default5]:    return forward_call(*args, **kwargs)
[default3]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[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
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default3]:    output = model(**micro_batch)
[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)
[default0]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 0 has a total capacity of 79.33 GiB of which 447.94 MiB is free. Including non-PyTorch memory, this process has 78.87 GiB memory in use. Of the allocated memory 70.11 GiB is allocated by PyTorch, and 52.08 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]:    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
[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
[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)
[default3]:    return self._call_impl(*args, **kwargs)
[default5]:    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
[default2]:  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)
[default2]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 562, in forward
[default2]:    key_value_states = torch.cat([key_states.unsqueeze(0), value_states.unsqueeze(0)], dim=0)
[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
[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 636, in forward
[default1]:Traceback (most recent call last):
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default2]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 64.00 MiB. GPU 2 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 69.99 GiB is allocated by PyTorch, and 53.09 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]:    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
[default1]:    trainer.train(dataloader)
[default5]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_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)
[default3]:    return forward_call(*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
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default5]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 171, in forward
[default3]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default5]:    hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[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)
[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
[default1]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default5]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[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
[default5]:    return forward_call(*args, **kwargs)
[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
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default5]:    return row_linear(
[default3]:    return self._call_impl(*args, **kwargs)
[default1]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default3]:    return forward_call(*args, **kwargs)
[default1]:    output = model(**micro_batch)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[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
[default3]:    output = self.pp_block(**new_kwargs)
[default1]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[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
[default5]:    out = F.linear(input, weight, bias)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 5 has a total capacity of 79.33 GiB of which 499.94 MiB is free. Including non-PyTorch memory, this process has 78.83 GiB memory in use. Of the allocated memory 69.30 GiB is allocated by PyTorch, and 21.12 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]:    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)
[default1]:    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
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[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)
[default1]:    sharded_logits = self.model(
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 597, in forward
[default3]:    output = self.o_proj(attention_output)
[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)
[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
[default1]:  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 self._call_impl(*args, **kwargs)
[default1]:    return forward_call(*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/tensor_parallel/nn.py", line 159, in forward
[default3]:    return row_linear(
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[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
[default3]:    out = F.linear(input, weight, bias)
[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)
[default3]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 3 has a total capacity of 79.33 GiB of which 19.94 MiB is free. Including non-PyTorch memory, this process has 79.29 GiB memory in use. Of the allocated memory 70.11 GiB is allocated by PyTorch, and 52.08 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]:  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 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]:  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 597, in forward
[default1]:    output = self.o_proj(attention_output)
[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/tensor_parallel/nn.py", line 159, in forward
[default1]:    return row_linear(
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default1]:    out = F.linear(input, weight, bias)
[default1]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 1 has a total capacity of 79.33 GiB of which 37.94 MiB is free. Including non-PyTorch memory, this process has 79.27 GiB memory in use. Of the allocated memory 70.11 GiB is allocated by PyTorch, and 52.08 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)
[2024-07-06 09:25:36,142] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 74095 closing signal SIGTERM
[2024-07-06 09:25:36,328] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 0 (pid: 59615) 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_09:25:36
  host      : ip-26-0-168-238.ec2.internal
  rank      : 9 (local_rank: 1)
  exitcode  : 1 (pid: 59616)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[2]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-238.ec2.internal
  rank      : 10 (local_rank: 2)
  exitcode  : 1 (pid: 59617)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[3]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-238.ec2.internal
  rank      : 11 (local_rank: 3)
  exitcode  : 1 (pid: 59618)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[4]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-238.ec2.internal
  rank      : 12 (local_rank: 4)
  exitcode  : 1 (pid: 59619)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[5]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-238.ec2.internal
  rank      : 13 (local_rank: 5)
  exitcode  : 1 (pid: 59620)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[6]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-238.ec2.internal
  rank      : 14 (local_rank: 6)
  exitcode  : 1 (pid: 59621)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[7]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-238.ec2.internal
  rank      : 15 (local_rank: 7)
  exitcode  : 1 (pid: 59622)
  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_09:25:36
  host      : ip-26-0-168-238.ec2.internal
  rank      : 8 (local_rank: 0)
  exitcode  : 1 (pid: 59615)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
srun: error: ip-26-0-168-238: task 1: Exited with exit code 1
[2024-07-06 09:25:37,379] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 1 (pid: 74096) 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_09:25:36
  host      : ip-26-0-168-120.ec2.internal
  rank      : 2 (local_rank: 2)
  exitcode  : 1 (pid: 74097)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[2]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-120.ec2.internal
  rank      : 3 (local_rank: 3)
  exitcode  : 1 (pid: 74098)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[3]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-120.ec2.internal
  rank      : 4 (local_rank: 4)
  exitcode  : 1 (pid: 74099)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[4]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-120.ec2.internal
  rank      : 5 (local_rank: 5)
  exitcode  : 1 (pid: 74100)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[5]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-120.ec2.internal
  rank      : 6 (local_rank: 6)
  exitcode  : 1 (pid: 74101)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[6]:
  time      : 2024-07-06_09:25:36
  host      : ip-26-0-168-120.ec2.internal
  rank      : 7 (local_rank: 7)
  exitcode  : 1 (pid: 74102)
  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_09:25:36
  host      : ip-26-0-168-120.ec2.internal
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 74096)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
srun: error: ip-26-0-168-120: task 0: Exited with exit code 1
[2024-07-06 09:25:40,154] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-169-86.ec2.internal_55895_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:25:40,947] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-171-168.ec2.internal_2809716_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:25:40,971] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-169-139.ec2.internal_454497_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:25:40,994] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-171-230.ec2.internal_3233845_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:25:41,017] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-169-207.ec2.internal_3353266_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:25:41,072] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-169-132.ec2.internal_57134_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:25:41,153] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3233914 closing signal SIGTERM
[2024-07-06 09:25:41,154] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3233915 closing signal SIGTERM
[2024-07-06 09:25:41,155] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 57202 closing signal SIGTERM
[2024-07-06 09:25:41,155] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 57203 closing signal SIGTERM
[2024-07-06 09:25:41,158] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 454566 closing signal SIGTERM
[2024-07-06 09:25:41,159] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 454567 closing signal SIGTERM
[2024-07-06 09:25:41,156] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 57204 closing signal SIGTERM
[2024-07-06 09:25:41,156] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3233916 closing signal SIGTERM
[2024-07-06 09:25:41,157] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 57205 closing signal SIGTERM
[2024-07-06 09:25:41,157] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2809785 closing signal SIGTERM
[2024-07-06 09:25:41,159] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3353334 closing signal SIGTERM
[2024-07-06 09:25:41,157] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2809786 closing signal SIGTERM
[2024-07-06 09:25:41,158] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 57206 closing signal SIGTERM
[2024-07-06 09:25:41,160] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 454568 closing signal SIGTERM
[2024-07-06 09:25:41,159] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3353335 closing signal SIGTERM
[2024-07-06 09:25:41,158] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 57207 closing signal SIGTERM
[2024-07-06 09:25:41,158] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3233917 closing signal SIGTERM
[2024-07-06 09:25:41,160] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3353336 closing signal SIGTERM
[2024-07-06 09:25:41,159] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2809787 closing signal SIGTERM
[2024-07-06 09:25:41,159] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2809788 closing signal SIGTERM
[2024-07-06 09:25:41,159] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2809789 closing signal SIGTERM
[2024-07-06 09:25:41,160] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 57208 closing signal SIGTERM
[2024-07-06 09:25:41,164] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 454569 closing signal SIGTERM
[2024-07-06 09:25:41,165] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 454570 closing signal SIGTERM
[2024-07-06 09:25:41,165] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 454571 closing signal SIGTERM
[2024-07-06 09:25:41,160] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3353337 closing signal SIGTERM
[2024-07-06 09:25:41,161] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 57209 closing signal SIGTERM
[2024-07-06 09:25:41,162] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3233918 closing signal SIGTERM
[2024-07-06 09:25:41,162] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3233919 closing signal SIGTERM
[2024-07-06 09:25:41,166] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 454572 closing signal SIGTERM
[2024-07-06 09:25:41,165] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3353338 closing signal SIGTERM
[2024-07-06 09:25:41,164] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2809790 closing signal SIGTERM
[2024-07-06 09:25:41,165] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3353339 closing signal SIGTERM
[2024-07-06 09:25:41,167] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 454573 closing signal SIGTERM
[2024-07-06 09:25:41,164] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3233920 closing signal SIGTERM
[2024-07-06 09:25:41,167] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3353340 closing signal SIGTERM
[2024-07-06 09:25:41,167] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3353341 closing signal SIGTERM
[2024-07-06 09:25:41,165] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3233921 closing signal SIGTERM
[2024-07-06 09:25:41,168] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2809791 closing signal SIGTERM
[2024-07-06 09:25:41,168] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2809792 closing signal SIGTERM
[2024-07-06 09:25:41,174] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 55964 closing signal SIGTERM
[2024-07-06 09:25:41,175] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 55965 closing signal SIGTERM
[2024-07-06 09:25:41,177] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 55966 closing signal SIGTERM
[2024-07-06 09:25:41,177] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 55967 closing signal SIGTERM
[2024-07-06 09:25:41,178] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 55968 closing signal SIGTERM
[2024-07-06 09:25:41,179] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 55969 closing signal SIGTERM
[2024-07-06 09:25:41,180] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 55970 closing signal SIGTERM
[2024-07-06 09:25:41,181] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 55971 closing signal SIGTERM
[2024-07-06 09:25:44,706] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-171-168.ec2.internal_2809716_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.
[2024-07-06 09:25:44,902] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-171-230.ec2.internal_3233845_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-26-0-171-168: task 6: Exited with exit code 1
srun: error: ip-26-0-171-230: task 7: Exited with exit code 1
[2024-07-06 09:25:45,158] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-169-86.ec2.internal_55895_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:25:45,304] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-169-207.ec2.internal_3353266_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.
[2024-07-06 09:25:45,517] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-169-139.ec2.internal_454497_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.
[2024-07-06 09:25:45,604] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-169-132.ec2.internal_57134_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
[2024-07-06 09:25:45,610] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-169-86.ec2.internal_55895_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
    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/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    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
    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>
    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
    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
    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
    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
    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
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
srun: error: ip-26-0-169-207: task 5: Exited with exit code 1
    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-26-0-169-139: task 4: Exited with exit code 1
srun: error: ip-26-0-169-132: task 3: Exited with exit code 1
srun: error: ip-26-0-169-86: task 2: 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.