llama-1B/64_GPUS/dp-1_tp-4_pp-16_mbz-2/log.out

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START TIME: Sat Jul  6 09:18:21 UTC 2024
python3 version = Python 3.10.14
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M	examples/config_tiny_llama.py
M	examples/config_tiny_llama.yaml
M	examples/train_tiny_llama.sh
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Job status: RUNNING
[2024-07-06 09:18:31,654] torch.distributed.run: [WARNING] 
[2024-07-06 09:18:31,654] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,654] 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 09:18:31,654] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,705] torch.distributed.run: [WARNING] 
[2024-07-06 09:18:31,705] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,705] 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 09:18:31,705] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,718] torch.distributed.run: [WARNING] 
[2024-07-06 09:18:31,718] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,718] 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 09:18:31,718] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,793] torch.distributed.run: [WARNING] 
[2024-07-06 09:18:31,793] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,793] 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 09:18:31,793] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,793] torch.distributed.run: [WARNING] 
[2024-07-06 09:18:31,793] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,793] 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 09:18:31,793] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,826] torch.distributed.run: [WARNING] 
[2024-07-06 09:18:31,826] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,826] 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 09:18:31,826] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,829] torch.distributed.run: [WARNING] 
[2024-07-06 09:18:31,829] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,829] 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 09:18:31,829] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,919] torch.distributed.run: [WARNING] 
[2024-07-06 09:18:31,919] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:18:31,919] 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 09:18:31,919] torch.distributed.run: [WARNING] *****************************************
[default0]:07/06/2024 09:18:53 [WARNING|DP=0|PP=0|TP=0|ip-26-0-161-221]: [Vocab Size Padding] Padded vocab (size: 50257) with 3 dummy tokens (new size: 50260)
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: Config:
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: Config(general=GeneralArgs(project='bench_cluster',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                            run='%date_%jobid',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                            seed=42,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                            step=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                            consumed_train_samples=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                            benchmark_csv_path=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                            ignore_sanity_checks=True),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:        parallelism=ParallelismArgs(dp=1,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                    pp=16,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                    tp=4,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                    pp_engine=<nanotron.parallel.pipeline_parallel.engine.AllForwardAllBackwardPipelineEngine object at 0x7fc4188308b0>,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                    tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                    tp_linear_async_communication=False,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                    expert_parallel_size=1),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:        model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 eos_token_id=2,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 hidden_act='silu',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 hidden_size=2048,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 initializer_range=0.02,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 intermediate_size=4096,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 is_llama_config=True,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 max_position_embeddings=4096,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 num_attention_heads=32,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 num_hidden_layers=24,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 num_key_value_heads=32,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 pad_token_id=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 pretraining_tp=1,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 rms_norm_eps=1e-05,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 rope_scaling=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 rope_theta=10000.0,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 tie_word_embeddings=True,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 use_cache=True,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                 vocab_size=50260),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                        init_method=RandomInit(std=0.025),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                        dtype=torch.bfloat16,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                        make_vocab_size_divisible_by=1,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                        ddp_bucket_cap_mb=25),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:        tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                tokenizer_revision=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                tokenizer_max_length=None),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:        checkpoints=CheckpointsArgs(checkpoints_path=PosixPath('/dev/null'),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                    checkpoint_interval=100000,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                    save_initial_state=False,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                    resume_checkpoint_path=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                    checkpoints_path_is_shared_file_system=False),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:        logging=LoggingArgs(log_level='info',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                            log_level_replica='info',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                            iteration_step_info_interval=1),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:        tokens=TokensArgs(sequence_length=4096,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                          train_steps=20,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                          micro_batch_size=2,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                          batch_accumulation_per_replica=512,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                          val_check_interval=-1,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                          limit_val_batches=0,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                          limit_test_batches=0),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:        optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                     adam_beta1=0.9,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                     adam_beta2=0.95,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                     torch_adam_is_fused=True,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                     name='adamW'),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                zero_stage=1,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                weight_decay=0.01,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                clip_grad=1.0,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                accumulate_grad_in_fp32=True,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                        lr_warmup_steps=1,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                        lr_warmup_style='linear',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                        lr_decay_style='linear',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                        lr_decay_steps=19,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                        lr_decay_starting_step=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                        min_decay_lr=1e-05)),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:        data_stages=[DatasetStageArgs(name='Training Stage',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                      start_training_step=1,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                      data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                                 hf_dataset_splits='train',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                                 hf_dataset_config_name=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                                 dataset_processing_num_proc_per_process=64,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                                 dataset_overwrite_cache=False,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                                                 text_column_name='text'),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                    seed=42,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:                                                    num_loading_workers=0))],
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:        profiler=ProfilerArgs(profiler_export_path=PosixPath('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/64_GPUS/dp-1_tp-4_pp-16_mbz-2')),
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:        lighteval=None)
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: Model Config:
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: LlamaConfig(bos_token_id=1,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             eos_token_id=2,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             hidden_act='silu',
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             hidden_size=2048,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             initializer_range=0.02,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             intermediate_size=4096,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             is_llama_config=True,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             max_position_embeddings=4096,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             num_attention_heads=32,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             num_hidden_layers=24,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             num_key_value_heads=32,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             pad_token_id=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             pretraining_tp=1,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             rms_norm_eps=1e-05,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             rope_scaling=None,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             rope_theta=10000.0,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             tie_word_embeddings=True,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             use_cache=True,
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:             vocab_size=50260)
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: Building model..
[default0]:07/06/2024 09:18:53 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: Setting PP block ranks...
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=1|ip-26-0-162-14]: Local number of parameters: 21M (40.02MiB)
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=1|ip-26-0-162-14]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=2|ip-26-0-167-9]: Local number of parameters: 25.7M (49.09MiB)
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=2|ip-26-0-167-9]: [After model building] Memory usage: 50.01MiB. Peak allocated: 50.03MiB Peak reserved: 52.00MiB
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=2|ip-26-0-167-9]: No checkpoint path provided.
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=0|ip-26-0-162-180]: Local number of parameters: 21M (40.02MiB)
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=0|ip-26-0-162-180]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=0|ip-26-0-162-180]: No checkpoint path provided.
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=3|ip-26-0-162-180]: Local number of parameters: 10.5M (20.01MiB)
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=3|ip-26-0-162-180]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=3|ip-26-0-162-180]: No checkpoint path provided.
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=2|ip-26-0-162-180]: Local number of parameters: 21M (40.02MiB)
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=2|ip-26-0-162-180]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=2|ip-26-0-162-180]: No checkpoint path provided.
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=1|ip-26-0-162-180]: Local number of parameters: 21M (40.02MiB)
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=1|ip-26-0-162-180]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=1|ip-26-0-162-180]: No checkpoint path provided.
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=0|ip-26-0-162-180]: Local number of parameters: 10.5M (20.01MiB)
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=0|ip-26-0-162-180]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=0|ip-26-0-162-180]: No checkpoint path provided.
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=1|ip-26-0-162-180]: Local number of parameters: 10.5M (20.01MiB)
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=1|ip-26-0-162-180]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=1|ip-26-0-162-180]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=3|ip-26-0-162-180]: Local number of parameters: 21M (40.02MiB)
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=3|ip-26-0-162-180]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=4|TP=3|ip-26-0-162-180]: No checkpoint path provided.
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=2|ip-26-0-162-180]: Local number of parameters: 10.5M (20.01MiB)
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=2|ip-26-0-162-180]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=5|TP=2|ip-26-0-162-180]: No checkpoint path provided.
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=0|ip-26-0-162-79]: Local number of parameters: 10.5M (20.01MiB)
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=0|ip-26-0-162-79]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=0|ip-26-0-162-79]: No checkpoint path provided.
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=1|ip-26-0-167-9]: Local number of parameters: 25.7M (49.09MiB)
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=1|ip-26-0-167-9]: [After model building] Memory usage: 50.01MiB. Peak allocated: 50.03MiB Peak reserved: 52.00MiB
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=1|ip-26-0-167-9]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=3|ip-26-0-167-9]: Local number of parameters: 25.7M (49.09MiB)
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=3|ip-26-0-167-9]: [After model building] Memory usage: 50.01MiB. Peak allocated: 50.03MiB Peak reserved: 52.00MiB
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=3|ip-26-0-167-9]: No checkpoint path provided.
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=1|ip-26-0-166-244]: Local number of parameters: 21M (40.02MiB)
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=1|ip-26-0-166-244]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=1|ip-26-0-166-244]: No checkpoint path provided.
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=0|ip-26-0-167-9]: Local number of parameters: 0 (0.00MiB)
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=0|ip-26-0-167-9]: [After model building] Memory usage: 0.01MiB. Peak allocated: 0.03MiB Peak reserved: 2.00MiB
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=0|ip-26-0-167-9]: No checkpoint path provided.
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=2|ip-26-0-167-9]: Local number of parameters: 0 (0.00MiB)
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=2|ip-26-0-167-9]: [After model building] Memory usage: 0.01MiB. Peak allocated: 0.03MiB Peak reserved: 2.00MiB
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=2|ip-26-0-167-9]: No checkpoint path provided.
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=0|ip-26-0-167-9]: Local number of parameters: 25.7M (49.09MiB)
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=0|ip-26-0-167-9]: [After model building] Memory usage: 50.01MiB. Peak allocated: 50.03MiB Peak reserved: 52.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=14|TP=0|ip-26-0-167-9]: No checkpoint path provided.
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=0|ip-26-0-162-14]: Local number of parameters: 10.5M (20.01MiB)
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=0|ip-26-0-162-14]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=0|ip-26-0-162-14]: No checkpoint path provided.
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=3|ip-26-0-162-79]: Local number of parameters: 21M (40.02MiB)
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=3|ip-26-0-162-79]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: Total number of parameters: 1.21G (2313.42MiB)
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: Local number of parameters: 46.7M (89.10MiB)
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: [After model building] Memory usage: 92.03MiB. Peak allocated: 94.06MiB Peak reserved: 96.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: No checkpoint path provided.
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: Parametrizing model parameters using StandardParametrizator
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=3|ip-26-0-162-79]: No checkpoint path provided.
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=0|ip-26-0-162-79]: Local number of parameters: 21M (40.02MiB)
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=0|ip-26-0-162-79]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=0|ip-26-0-162-79]: No checkpoint path provided.
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=1|ip-26-0-162-79]: Local number of parameters: 10.5M (20.01MiB)
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=1|ip-26-0-162-79]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=1|ip-26-0-162-79]: No checkpoint path provided.
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-221]: Local number of parameters: 21M (40.02MiB)
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-221]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-221]: No checkpoint path provided.
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-221]: Local number of parameters: 21M (40.02MiB)
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-221]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=2|ip-26-0-166-244]: Local number of parameters: 21M (40.02MiB)
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=3|ip-26-0-162-14]: Local number of parameters: 21M (40.02MiB)
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=3|ip-26-0-162-46]: Local number of parameters: 21M (40.02MiB)
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=3|ip-26-0-162-46]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=3|ip-26-0-162-46]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=3|ip-26-0-162-79]: Local number of parameters: 10.5M (20.01MiB)
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=3|ip-26-0-162-14]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=3|ip-26-0-162-14]: No checkpoint path provided.
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=2|ip-26-0-166-244]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=2|ip-26-0-166-244]: No checkpoint path provided.
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-221]: No checkpoint path provided.
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=2|ip-26-0-161-221]: Local number of parameters: 46.7M (89.10MiB)
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=2|ip-26-0-161-221]: [After model building] Memory usage: 92.03MiB. Peak allocated: 94.06MiB Peak reserved: 96.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=0|ip-26-0-162-46]: Local number of parameters: 21M (40.02MiB)
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=3|ip-26-0-162-79]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-221]: Local number of parameters: 46.7M (89.10MiB)
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=0|ip-26-0-162-46]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=0|ip-26-0-162-46]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=3|ip-26-0-162-79]: No checkpoint path provided.
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-221]: [After model building] Memory usage: 92.03MiB. Peak allocated: 94.06MiB Peak reserved: 96.00MiB
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=2|ip-26-0-161-221]: Local number of parameters: 21M (40.02MiB)
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=2|ip-26-0-162-79]: Local number of parameters: 21M (40.02MiB)
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=2|ip-26-0-162-79]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=2|ip-26-0-161-221]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=2|ip-26-0-162-14]: Local number of parameters: 10.5M (20.01MiB)
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=2|ip-26-0-162-79]: No checkpoint path provided.
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=2|ip-26-0-161-221]: No checkpoint path provided.
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=2|ip-26-0-162-79]: Local number of parameters: 10.5M (20.01MiB)
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=2|ip-26-0-162-79]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=2|ip-26-0-161-221]: No checkpoint path provided.
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=8|TP=2|ip-26-0-162-79]: No checkpoint path provided.
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-221]: No checkpoint path provided.
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=2|ip-26-0-162-14]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=2|ip-26-0-166-244]: Local number of parameters: 21M (40.02MiB)
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=2|ip-26-0-166-244]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=0|ip-26-0-162-14]: Local number of parameters: 21M (40.02MiB)
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=1|ip-26-0-162-14]: Local number of parameters: 10.5M (20.01MiB)
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=1|ip-26-0-162-14]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=2|ip-26-0-166-244]: No checkpoint path provided.
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=2|ip-26-0-162-14]: No checkpoint path provided.
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=1|ip-26-0-162-14]: No checkpoint path provided.
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=0|ip-26-0-162-14]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=0|ip-26-0-162-14]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=3|ip-26-0-166-214]: Local number of parameters: 21M (40.02MiB)
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=3|ip-26-0-166-214]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=0|ip-26-0-166-244]: Local number of parameters: 21M (40.02MiB)
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=0|ip-26-0-166-244]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=0|ip-26-0-166-244]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=3|ip-26-0-161-221]: Local number of parameters: 46.7M (89.10MiB)
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=3|ip-26-0-166-214]: No checkpoint path provided.
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=2|ip-26-0-166-214]: Local number of parameters: 21M (40.02MiB)
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=2|ip-26-0-166-214]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=2|ip-26-0-166-214]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=3|ip-26-0-161-221]: [After model building] Memory usage: 92.03MiB. Peak allocated: 94.06MiB Peak reserved: 96.00MiB
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=0|TP=3|ip-26-0-161-221]: No checkpoint path provided.
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=3|ip-26-0-161-221]: Local number of parameters: 21M (40.02MiB)
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=3|ip-26-0-161-221]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=1|TP=3|ip-26-0-161-221]: No checkpoint path provided.
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=1|ip-26-0-166-214]: Local number of parameters: 21M (40.02MiB)
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=1|ip-26-0-166-214]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=1|ip-26-0-166-214]: No checkpoint path provided.
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=3|ip-26-0-166-214]: Local number of parameters: 10.5M (20.01MiB)
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=1|ip-26-0-162-79]: Local number of parameters: 21M (40.02MiB)
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=1|ip-26-0-162-79]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=9|TP=1|ip-26-0-162-79]: No checkpoint path provided.
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=0|ip-26-0-166-214]: Local number of parameters: 10.5M (20.01MiB)
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=0|ip-26-0-166-214]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=0|ip-26-0-166-214]: No checkpoint path provided.
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=3|ip-26-0-166-214]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=3|ip-26-0-166-214]: No checkpoint path provided.
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=1|ip-26-0-166-214]: Local number of parameters: 10.5M (20.01MiB)
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=3|ip-26-0-162-46]: Local number of parameters: 21M (40.02MiB)
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=1|ip-26-0-162-46]: Local number of parameters: 21M (40.02MiB)
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=1|ip-26-0-166-214]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=1|ip-26-0-166-214]: No checkpoint path provided.
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=1|ip-26-0-162-46]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=1|ip-26-0-162-46]: No checkpoint path provided.
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=0|ip-26-0-166-214]: Local number of parameters: 21M (40.02MiB)
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=0|ip-26-0-166-214]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default0]:07/06/2024 09:19:10 [INFO|DP=0|PP=10|TP=0|ip-26-0-166-214]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=3|ip-26-0-162-46]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=2|ip-26-0-162-46]: Local number of parameters: 21M (40.02MiB)
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=2|ip-26-0-162-46]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default2]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=2|ip-26-0-162-46]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=6|TP=3|ip-26-0-162-46]: No checkpoint path provided.
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=0|ip-26-0-162-46]: Local number of parameters: 21M (40.02MiB)
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=0|ip-26-0-162-46]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=0|ip-26-0-162-46]: No checkpoint path provided.
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=2|ip-26-0-162-46]: Local number of parameters: 21M (40.02MiB)
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=2|ip-26-0-162-46]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=2|ip-26-0-162-46]: No checkpoint path provided.
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=3|ip-26-0-166-244]: Local number of parameters: 21M (40.02MiB)
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=3|ip-26-0-166-244]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=3|ip-26-0-166-244]: No checkpoint path provided.
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=1|ip-26-0-166-244]: Local number of parameters: 21M (40.02MiB)
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=1|ip-26-0-166-244]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default1]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=1|ip-26-0-166-244]: No checkpoint path provided.
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=0|ip-26-0-166-244]: Local number of parameters: 21M (40.02MiB)
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=0|ip-26-0-166-244]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default4]:07/06/2024 09:19:10 [INFO|DP=0|PP=13|TP=0|ip-26-0-166-244]: No checkpoint path provided.
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=3|ip-26-0-167-9]: Local number of parameters: 0 (0.00MiB)
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=3|ip-26-0-167-9]: [After model building] Memory usage: 0.01MiB. Peak allocated: 0.03MiB Peak reserved: 2.00MiB
[default7]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=3|ip-26-0-167-9]: No checkpoint path provided.
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=2|ip-26-0-166-214]: Local number of parameters: 10.5M (20.01MiB)
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=2|ip-26-0-166-214]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=11|TP=2|ip-26-0-166-214]: No checkpoint path provided.
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=1|ip-26-0-162-46]: Local number of parameters: 21M (40.02MiB)
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=1|ip-26-0-162-46]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=7|TP=1|ip-26-0-162-46]: No checkpoint path provided.
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=2|ip-26-0-162-14]: Local number of parameters: 21M (40.02MiB)
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=2|ip-26-0-162-14]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default6]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=2|ip-26-0-162-14]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=3|ip-26-0-166-244]: Local number of parameters: 21M (40.02MiB)
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=3|ip-26-0-166-244]: [After model building] Memory usage: 42.03MiB. Peak allocated: 44.06MiB Peak reserved: 46.00MiB
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=12|TP=3|ip-26-0-166-244]: No checkpoint path provided.
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=3|ip-26-0-162-14]: Local number of parameters: 10.5M (20.01MiB)
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=3|ip-26-0-162-14]: [After model building] Memory usage: 21.02MiB. Peak allocated: 23.05MiB Peak reserved: 24.00MiB
[default3]:07/06/2024 09:19:10 [INFO|DP=0|PP=2|TP=3|ip-26-0-162-14]: No checkpoint path provided.
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=1|ip-26-0-167-9]: Local number of parameters: 0 (0.00MiB)
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=1|ip-26-0-167-9]: [After model building] Memory usage: 0.01MiB. Peak allocated: 0.03MiB Peak reserved: 2.00MiB
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=15|TP=1|ip-26-0-167-9]: No checkpoint path provided.
[default5]:07/06/2024 09:19:10 [INFO|DP=0|PP=3|TP=1|ip-26-0-162-14]: No checkpoint path provided.
[default0]:07/06/2024 09:19:11 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: [Optimizer Building] Using LearningRateForSP as learning rate
[default0]:07/06/2024 09:19:11 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: [ZeRO sharding] Size of optimizer params per rank:
[default0]:07/06/2024 09:19:11 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: [ZeRO sharding] DP Rank 0 has 46.7M out of 46.7M (100.00%) params' optimizer states
[default0]:07/06/2024 09:19:12 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
[default0]:07/06/2024 09:19:12 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: Using `datasets` library
[default0]:07/06/2024 09:19:12 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: 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 09:19:13 [WARNING|DP=0|PP=0|TP=0|ip-26-0-161-221]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:19:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: [Training Plan] There are 1 training stages 
[default0]:07/06/2024 09:19:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: [Stage Training Stage] start from step 1 
[default0]:07/06/2024 09:19:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: 
[default0]:07/06/2024 09:19:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: [Start training] datetime: 2024-07-06 09:19:15.112356 | mbs: 2 | grad_accum: 512 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
[default7]:07/06/2024 09:19:15 [WARNING|DP=0|PP=5|TP=3|ip-26-0-162-180]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:19:15 [WARNING|DP=0|PP=4|TP=1|ip-26-0-162-180]: 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 09:19:15 [WARNING|DP=0|PP=15|TP=0|ip-26-0-167-9]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:19:15 [WARNING|DP=0|PP=13|TP=2|ip-26-0-166-244]: 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.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:19:15 [WARNING|DP=0|PP=0|TP=2|ip-26-0-161-221]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:19:15 [WARNING|DP=0|PP=1|TP=1|ip-26-0-161-221]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:19:15 [WARNING|DP=0|PP=3|TP=0|ip-26-0-162-14]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:19:15 [WARNING|DP=0|PP=0|TP=1|ip-26-0-161-221]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:19:15 [WARNING|DP=0|PP=1|TP=2|ip-26-0-161-221]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:19:15 [WARNING|DP=0|PP=10|TP=1|ip-26-0-166-214]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:19:15 [WARNING|DP=0|PP=1|TP=3|ip-26-0-161-221]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:19:15 [WARNING|DP=0|PP=7|TP=0|ip-26-0-162-46]: 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.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:19:15 [WARNING|DP=0|PP=13|TP=0|ip-26-0-166-244]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:19:15 [WARNING|DP=0|PP=12|TP=1|ip-26-0-166-244]: 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.
[default3]:07/06/2024 09:19:15 [WARNING|DP=0|PP=12|TP=3|ip-26-0-166-244]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:19:15 [WARNING|DP=0|PP=2|TP=3|ip-26-0-162-14]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:19:15 [WARNING|DP=0|PP=15|TP=1|ip-26-0-167-9]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:19:15 [WARNING|DP=0|PP=3|TP=1|ip-26-0-162-14]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:19:15 [WARNING|DP=0|PP=4|TP=0|ip-26-0-162-180]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:19:15 [WARNING|DP=0|PP=5|TP=0|ip-26-0-162-180]: 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.
[default5]:07/06/2024 09:19:15 [WARNING|DP=0|PP=5|TP=1|ip-26-0-162-180]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:19:15 [WARNING|DP=0|PP=5|TP=2|ip-26-0-162-180]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:19:15 [WARNING|DP=0|PP=4|TP=3|ip-26-0-162-180]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:19:15 [WARNING|DP=0|PP=13|TP=1|ip-26-0-166-244]: 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 09:19:15 [WARNING|DP=0|PP=8|TP=0|ip-26-0-162-79]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:19:15 [WARNING|DP=0|PP=14|TP=1|ip-26-0-167-9]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:19:15 [WARNING|DP=0|PP=14|TP=3|ip-26-0-167-9]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:19:15 [WARNING|DP=0|PP=2|TP=0|ip-26-0-162-14]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:19:15 [WARNING|DP=0|PP=15|TP=2|ip-26-0-167-9]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:19:15 [WARNING|DP=0|PP=14|TP=0|ip-26-0-167-9]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:19:15 [WARNING|DP=0|PP=3|TP=3|ip-26-0-162-14]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:19:15 [WARNING|DP=0|PP=9|TP=0|ip-26-0-162-79]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:19:15 [WARNING|DP=0|PP=8|TP=1|ip-26-0-162-79]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:19:15 [WARNING|DP=0|PP=9|TP=3|ip-26-0-162-79]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:19:15 [WARNING|DP=0|PP=6|TP=0|ip-26-0-162-46]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:19:15 [WARNING|DP=0|PP=8|TP=2|ip-26-0-162-79]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:19:15 [WARNING|DP=0|PP=7|TP=3|ip-26-0-162-46]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:19:15 [WARNING|DP=0|PP=9|TP=2|ip-26-0-162-79]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:19:15 [WARNING|DP=0|PP=8|TP=3|ip-26-0-162-79]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:19:15 [WARNING|DP=0|PP=1|TP=0|ip-26-0-161-221]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:19:15 [WARNING|DP=0|PP=12|TP=2|ip-26-0-166-244]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:19:15 [WARNING|DP=0|PP=2|TP=2|ip-26-0-162-14]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:19:15 [WARNING|DP=0|PP=2|TP=1|ip-26-0-162-14]: Repo card metadata block was not found. Setting CardData to empty.
[default2]: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.
[default2]:07/06/2024 09:19:15 [WARNING|DP=0|PP=10|TP=2|ip-26-0-166-214]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:19:15 [WARNING|DP=0|PP=12|TP=0|ip-26-0-166-244]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:19:15 [WARNING|DP=0|PP=10|TP=3|ip-26-0-166-214]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:19:15 [WARNING|DP=0|PP=11|TP=3|ip-26-0-166-214]: 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 09:19:15 [WARNING|DP=0|PP=11|TP=0|ip-26-0-166-214]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:19:15 [WARNING|DP=0|PP=9|TP=1|ip-26-0-162-79]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:19:15 [WARNING|DP=0|PP=0|TP=3|ip-26-0-161-221]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:19:15 [WARNING|DP=0|PP=6|TP=1|ip-26-0-162-46]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:19:15 [WARNING|DP=0|PP=11|TP=1|ip-26-0-166-214]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:19:15 [WARNING|DP=0|PP=6|TP=2|ip-26-0-162-46]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:19:15 [WARNING|DP=0|PP=6|TP=3|ip-26-0-162-46]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:19:15 [WARNING|DP=0|PP=10|TP=0|ip-26-0-166-214]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:19:15 [WARNING|DP=0|PP=13|TP=3|ip-26-0-166-244]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:19:15 [WARNING|DP=0|PP=15|TP=3|ip-26-0-167-9]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:19:15 [WARNING|DP=0|PP=11|TP=2|ip-26-0-166-214]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:19:15 [WARNING|DP=0|PP=7|TP=1|ip-26-0-162-46]: 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.
[default6]:07/06/2024 09:19:15 [WARNING|DP=0|PP=3|TP=2|ip-26-0-162-14]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:19:15 [WARNING|DP=0|PP=4|TP=2|ip-26-0-162-180]: Repo card metadata block was not found. Setting CardData to empty.
[default2]: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 09:19:15 [WARNING|DP=0|PP=14|TP=2|ip-26-0-167-9]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:19:15 [WARNING|DP=0|PP=7|TP=2|ip-26-0-162-46]: 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 09:19:23 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
[default0]:07/06/2024 09:19:23 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-221]:  Memory usage: 448.42MiB. Peak allocated 448.42MiB. Peak reserved: 456.00MiB
[default5]:Traceback (most recent call last):
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default5]:    trainer.train(dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default5]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default5]:    outputs = self.pipeline_engine.train_batch_iter(
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default5]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default5]:    output = model(**micro_batch)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 894, in forward
[default5]:    loss = self.loss(
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default5]:    output = self.pp_block(**new_kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 848, in forward
[default5]:    loss = sharded_cross_entropy(
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 116, in sharded_cross_entropy
[default5]:    return _ShardedCrossEntropy.apply(sharded_logits, target, group)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/function.py", line 553, in apply
[default5]:    return super().apply(*args, **kwargs)  # type: ignore[misc]
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 44, in forward
[default5]:    sharded_logits = sharded_logits - logits_max.unsqueeze(dim=-1)
[default5]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 394.00 MiB. GPU 5 has a total capacity of 79.33 GiB of which 381.94 MiB is free. Including non-PyTorch memory, this process has 78.95 GiB memory in use. Of the allocated memory 69.03 GiB is allocated by PyTorch, and 440.29 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 479, in row_linear
[default6]:    out = differentiable_reduce_scatter_sum(out, group=group)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py", line 145, in differentiable_reduce_scatter_sum
[default6]:    return DifferentiableReduceScatterSum.apply(tensor, group)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/function.py", line 553, in apply
[default6]:    return super().apply(*args, **kwargs)  # type: ignore[misc]
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py", line 111, in forward
[default6]:    sharded_tensor = torch.empty(
[default6]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 6 has a total capacity of 79.33 GiB of which 13.94 MiB is free. Including non-PyTorch memory, this process has 79.30 GiB memory in use. Of the allocated memory 67.94 GiB is allocated by PyTorch, and 1.36 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default2]:Traceback (most recent call last):
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default2]:    trainer.train(dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default2]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default2]:    outputs = self.pipeline_engine.train_batch_iter(
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default2]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default2]:    output = model(**micro_batch)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default2]:    sharded_logits = self.model(
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default2]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default2]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default2]:    output = self.pp_block(**new_kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 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 597, in forward
[default2]:    output = self.o_proj(attention_output)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default2]:    return row_linear(
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default2]:    out = F.linear(input, weight, bias)
[default2]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 2 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 68.67 GiB is allocated by PyTorch, and 1.03 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default5]:Traceback (most recent call last):
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default5]:    trainer.train(dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default5]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default1]:Traceback (most recent call last):
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[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
[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
[default5]:    output = model(**micro_batch)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[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
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default5]:    sharded_logits = self.model(
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default5]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default5]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[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)
[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
[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]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default5]:    output = self.pp_block(**new_kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 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
[default5]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default1]:    sharded_logits = self.model(
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[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]:    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]:    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)
[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)
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default1]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default1]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, 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]:    return row_linear(
[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
[default1]:    return forward_call(*args, **kwargs)
[default5]:    out = F.linear(input, weight, bias)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default1]:    output = self.pp_block(**new_kwargs)
[default1]:  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]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 5 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 67.91 GiB is allocated by PyTorch, and 1.36 GiB 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 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 636, in forward
[default1]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 171, in forward
[default1]:    hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/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 32.00 MiB. GPU 1 has a total capacity of 79.33 GiB of which 25.94 MiB is free. Including non-PyTorch memory, this process has 79.29 GiB memory in use. Of the allocated memory 68.75 GiB is allocated by PyTorch, and 1.03 GiB 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 09:20:24,212] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 173947 closing signal SIGTERM
[2024-07-06 09:20:24,212] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 173950 closing signal SIGTERM
[2024-07-06 09:20:24,213] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 173951 closing signal SIGTERM
[2024-07-06 09:20:24,214] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 173954 closing signal SIGTERM
[2024-07-06 09:20:24,216] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2812318 closing signal SIGTERM
[2024-07-06 09:20:24,217] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2812319 closing signal SIGTERM
[2024-07-06 09:20:24,220] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2812320 closing signal SIGTERM
[2024-07-06 09:20:24,220] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2812321 closing signal SIGTERM
[2024-07-06 09:20:24,220] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2812322 closing signal SIGTERM
[2024-07-06 09:20:24,221] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2812324 closing signal SIGTERM
[2024-07-06 09:20:24,224] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2812325 closing signal SIGTERM
[2024-07-06 09:20:26,977] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 5 (pid: 2812323) 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:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-07-06_09:20:24
  host      : ip-26-0-167-9.ec2.internal
  rank      : 61 (local_rank: 5)
  exitcode  : 1 (pid: 2812323)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
srun: error: ip-26-0-167-9: task 7: Exited with exit code 1
[2024-07-06 09:20:27,268] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 1 (pid: 173948) 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_09:20:24
  host      : ip-26-0-161-221.ec2.internal
  rank      : 2 (local_rank: 2)
  exitcode  : 1 (pid: 173949)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[2]:
  time      : 2024-07-06_09:20:24
  host      : ip-26-0-161-221.ec2.internal
  rank      : 5 (local_rank: 5)
  exitcode  : 1 (pid: 173952)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[3]:
  time      : 2024-07-06_09:20:24
  host      : ip-26-0-161-221.ec2.internal
  rank      : 6 (local_rank: 6)
  exitcode  : 1 (pid: 173953)
  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_09:20:24
  host      : ip-26-0-161-221.ec2.internal
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 173948)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
srun: error: ip-26-0-161-221: task 0: Exited with exit code 1
[2024-07-06 09:20:28,210] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-166-214.ec2.internal_178857_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:28,360] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-79.ec2.internal_1034639_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:28,934] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-166-244.ec2.internal_4115841_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:28,981] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-180.ec2.internal_221438_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:29,048] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-46.ec2.internal_1296024_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:29,178] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-14.ec2.internal_1189772_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:29,216] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 4115918 closing signal SIGTERM
[2024-07-06 09:20:29,217] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 4115919 closing signal SIGTERM
[2024-07-06 09:20:29,218] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 4115920 closing signal SIGTERM
[2024-07-06 09:20:29,219] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 4115921 closing signal SIGTERM
[2024-07-06 09:20:29,220] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 4115922 closing signal SIGTERM
[2024-07-06 09:20:29,220] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 4115923 closing signal SIGTERM
[2024-07-06 09:20:29,221] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 4115924 closing signal SIGTERM
[2024-07-06 09:20:29,221] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 4115925 closing signal SIGTERM
[2024-07-06 09:20:29,222] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1296101 closing signal SIGTERM
[2024-07-06 09:20:29,222] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1296102 closing signal SIGTERM
[2024-07-06 09:20:29,224] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1296103 closing signal SIGTERM
[2024-07-06 09:20:29,224] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1296104 closing signal SIGTERM
[2024-07-06 09:20:29,224] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1296105 closing signal SIGTERM
[2024-07-06 09:20:29,225] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1296106 closing signal SIGTERM
[2024-07-06 09:20:29,225] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1296107 closing signal SIGTERM
[2024-07-06 09:20:29,226] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1296108 closing signal SIGTERM
[2024-07-06 09:20:29,229] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 221514 closing signal SIGTERM
[2024-07-06 09:20:29,230] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 221515 closing signal SIGTERM
[2024-07-06 09:20:29,230] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1034714 closing signal SIGTERM
[2024-07-06 09:20:29,230] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1189849 closing signal SIGTERM
[2024-07-06 09:20:29,231] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1034715 closing signal SIGTERM
[2024-07-06 09:20:29,230] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1189850 closing signal SIGTERM
[2024-07-06 09:20:29,230] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 221516 closing signal SIGTERM
[2024-07-06 09:20:29,231] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1034716 closing signal SIGTERM
[2024-07-06 09:20:29,231] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1189851 closing signal SIGTERM
[2024-07-06 09:20:29,231] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 221517 closing signal SIGTERM
[2024-07-06 09:20:29,232] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1189852 closing signal SIGTERM
[2024-07-06 09:20:29,232] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1189853 closing signal SIGTERM
[2024-07-06 09:20:29,232] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1189854 closing signal SIGTERM
[2024-07-06 09:20:29,233] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1034717 closing signal SIGTERM
[2024-07-06 09:20:29,231] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 221518 closing signal SIGTERM
[2024-07-06 09:20:29,234] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1034718 closing signal SIGTERM
[2024-07-06 09:20:29,234] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1189855 closing signal SIGTERM
[2024-07-06 09:20:29,234] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 221519 closing signal SIGTERM
[2024-07-06 09:20:29,235] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1034719 closing signal SIGTERM
[2024-07-06 09:20:29,235] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1189856 closing signal SIGTERM
[2024-07-06 09:20:29,235] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1034720 closing signal SIGTERM
[2024-07-06 09:20:29,235] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 221520 closing signal SIGTERM
[2024-07-06 09:20:29,236] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1034721 closing signal SIGTERM
[2024-07-06 09:20:29,236] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 221521 closing signal SIGTERM
[2024-07-06 09:20:29,241] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 178932 closing signal SIGTERM
[2024-07-06 09:20:29,241] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 178933 closing signal SIGTERM
[2024-07-06 09:20:29,242] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 178934 closing signal SIGTERM
[2024-07-06 09:20:29,242] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 178935 closing signal SIGTERM
[2024-07-06 09:20:29,242] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 178936 closing signal SIGTERM
[2024-07-06 09:20:29,243] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 178937 closing signal SIGTERM
[2024-07-06 09:20:29,243] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 178938 closing signal SIGTERM
[2024-07-06 09:20:29,243] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 178939 closing signal SIGTERM
[2024-07-06 09:20:33,216] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-166-214.ec2.internal_178857_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:33,364] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-79.ec2.internal_1034639_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:33,939] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-166-244.ec2.internal_4115841_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:33,986] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-166-214.ec2.internal_178857_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:33,985] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-180.ec2.internal_221438_0' has failed to send a keep-alive heartbeat to 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 09:20:34,053] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-46.ec2.internal_1296024_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:34,089] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-79.ec2.internal_1034639_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:20:34,088] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-166-244.ec2.internal_4115841_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
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>
    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
    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
    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
    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__
    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
    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 = 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 = 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
    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
    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
    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
    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
    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
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
    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 09:20:34,179] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-180.ec2.internal_221438_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__
[2024-07-06 09:20:34,182] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-14.ec2.internal_1189772_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
    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 09:20:34,289] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-14.ec2.internal_1189772_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-26-0-166-214: task 5: Exited with exit code 1
srun: error: ip-26-0-162-180: task 4: Exited with exit code 1
srun: error: ip-26-0-162-79: task 3: Exited with exit code 1
srun: error: ip-26-0-166-244: task 6: Exited with exit code 1
srun: error: ip-26-0-162-14: task 1: Exited with exit code 1
[2024-07-06 09:20:34,690] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-162-46.ec2.internal_1296024_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-26-0-162-46: task 2: Exited with exit code 1
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