llama-1B/8_GPUS/dp-4_tp-2_pp-1_mbz-2/log.out

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START TIME: Wed Jul  3 21:28:21 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
M	src/nanotron/models/llama.py
M	src/nanotron/trainer.py
Your branch is up to date with 'origin/bench_cluster'.
Job status: RUNNING
W0703 21:28:23.974000 140195712452416 torch/distributed/run.py:757] 
W0703 21:28:23.974000 140195712452416 torch/distributed/run.py:757] *****************************************
W0703 21:28:23.974000 140195712452416 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0703 21:28:23.974000 140195712452416 torch/distributed/run.py:757] *****************************************
[default0]:07/03/2024 21:28:40 [WARNING|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Vocab Size Padding] Padded vocab (size: 50257) with 1 dummy tokens (new size: 50258)
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Config:
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Config(general=GeneralArgs(project='bench_cluster',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            run='%date_%jobid',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            seed=42,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            step=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            consumed_train_samples=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            benchmark_csv_path=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            ignore_sanity_checks=True),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        parallelism=ParallelismArgs(dp=4,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    pp=1,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    tp=2,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7f3e420e4820>,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    tp_linear_async_communication=False,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    expert_parallel_size=1),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 eos_token_id=2,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 hidden_act='silu',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 hidden_size=2048,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 initializer_range=0.02,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 intermediate_size=4096,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 is_llama_config=True,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 max_position_embeddings=4096,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 num_attention_heads=32,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 num_hidden_layers=24,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 num_key_value_heads=32,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 pad_token_id=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 pretraining_tp=1,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 rms_norm_eps=1e-05,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 rope_scaling=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 rope_theta=10000.0,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 tie_word_embeddings=True,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 use_cache=True,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 vocab_size=50258),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                        init_method=RandomInit(std=0.025),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                        dtype=torch.bfloat16,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                        make_vocab_size_divisible_by=1,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                        ddp_bucket_cap_mb=25),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                tokenizer_revision=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                tokenizer_max_length=None),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    checkpoint_interval=100000,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    save_initial_state=False,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    resume_checkpoint_path=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    checkpoints_path_is_shared_file_system=False),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        logging=LoggingArgs(log_level='info',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            log_level_replica='info',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            iteration_step_info_interval=1),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        tokens=TokensArgs(sequence_length=4096,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          train_steps=20,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          micro_batch_size=2,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          batch_accumulation_per_replica=128,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          val_check_interval=-1,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          limit_val_batches=0,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          limit_test_batches=0),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                     adam_beta1=0.9,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                     adam_beta2=0.95,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                     torch_adam_is_fused=True,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                     name='adamW'),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                zero_stage=1,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                weight_decay=0.01,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                clip_grad=1.0,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                accumulate_grad_in_fp32=True,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        lr_warmup_steps=1,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        lr_warmup_style='linear',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        lr_decay_style='linear',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        lr_decay_steps=19,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        lr_decay_starting_step=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        min_decay_lr=1e-05)),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        data_stages=[DatasetStageArgs(name='Training Stage',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                      start_training_step=1,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                      data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                                 hf_dataset_splits='train',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                                 hf_dataset_config_name=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                                 dataset_processing_num_proc_per_process=64,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                                 dataset_overwrite_cache=False,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                                 text_column_name='text'),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                    seed=42,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                    num_loading_workers=0))],
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-4_tp-2_pp-1_mbz-2')),
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        lighteval=None)
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Model Config:
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: LlamaConfig(bos_token_id=1,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             eos_token_id=2,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             hidden_act='silu',
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             hidden_size=2048,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             initializer_range=0.02,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             intermediate_size=4096,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             is_llama_config=True,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             max_position_embeddings=4096,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             num_attention_heads=32,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             num_hidden_layers=24,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             num_key_value_heads=32,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             pad_token_id=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             pretraining_tp=1,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             rms_norm_eps=1e-05,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             rope_scaling=None,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             rope_theta=10000.0,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             tie_word_embeddings=True,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             use_cache=True,
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             vocab_size=50258)
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Building model..
[default0]:07/03/2024 21:28:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Setting PP block ranks...
[default1]:07/03/2024 21:28:50 [INFO|DP=0|PP=0|TP=1|ip-26-0-174-36]: Local number of parameters: 555M (1058.35MiB)
[default1]:07/03/2024 21:28:50 [INFO|DP=0|PP=0|TP=1|ip-26-0-174-36]: [After model building] Memory usage: 1082.37MiB. Peak allocated: 1182.56MiB Peak reserved: 1200.00MiB
[default1]:07/03/2024 21:28:50 [INFO|DP=0|PP=0|TP=1|ip-26-0-174-36]: No checkpoint path provided.
[default0]:07/03/2024 21:28:50 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Total number of parameters: 1.11G (2116.70MiB)
[default0]:07/03/2024 21:28:50 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Local number of parameters: 555M (1058.35MiB)
[default0]:07/03/2024 21:28:50 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [After model building] Memory usage: 1082.37MiB. Peak allocated: 1182.56MiB Peak reserved: 1200.00MiB
[default0]:07/03/2024 21:28:50 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: No checkpoint path provided.
[default0]:07/03/2024 21:28:50 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Parametrizing model parameters using StandardParametrizator
[default2]:07/03/2024 21:28:50 [INFO|DP=1|PP=0|TP=0|ip-26-0-174-36]: No checkpoint path provided.
[default3]:07/03/2024 21:28:50 [INFO|DP=1|PP=0|TP=1|ip-26-0-174-36]: No checkpoint path provided.
[default4]:07/03/2024 21:28:50 [INFO|DP=2|PP=0|TP=0|ip-26-0-174-36]: No checkpoint path provided.
[default5]:07/03/2024 21:28:50 [INFO|DP=2|PP=0|TP=1|ip-26-0-174-36]: No checkpoint path provided.
[default6]:07/03/2024 21:28:50 [INFO|DP=3|PP=0|TP=0|ip-26-0-174-36]: No checkpoint path provided.
[default7]:07/03/2024 21:28:50 [INFO|DP=3|PP=0|TP=1|ip-26-0-174-36]: No checkpoint path provided.
[default0]:07/03/2024 21:28:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Optimizer Building] Using LearningRateForSP as learning rate
[default0]:07/03/2024 21:28:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [ZeRO sharding] Size of optimizer params per rank:
[default0]:07/03/2024 21:28:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [ZeRO sharding] DP Rank 0 has 139M out of 555M (25.00%) params' optimizer states
[default0]:07/03/2024 21:28:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [ZeRO sharding] DP Rank 1 has 139M out of 555M (25.00%) params' optimizer states
[default0]:07/03/2024 21:28:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [ZeRO sharding] DP Rank 2 has 139M out of 555M (25.00%) params' optimizer states
[default0]:07/03/2024 21:28:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [ZeRO sharding] DP Rank 3 has 139M out of 555M (25.00%) params' optimizer states
[default0]:07/03/2024 21:28:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
[default0]:07/03/2024 21:28:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Using `datasets` library
[default0]:07/03/2024 21:28:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
[default0]:07/03/2024 21:28:56 [WARNING|DP=0|PP=0|TP=0|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/03/2024 21:28:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Training Plan] There are 1 training stages 
[default0]:07/03/2024 21:28:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Stage Training Stage] start from step 1 
[default0]:07/03/2024 21:28:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: 
[default0]:07/03/2024 21:28:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Start training] datetime: 2024-07-03 21:28:57.058405 | mbs: 2 | grad_accum: 128 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
[default0]:07/03/2024 21:28:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
[default0]:07/03/2024 21:28:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 3729.08MiB. Peak allocated 3729.08MiB. Peak reserved: 3848.00MiB
[default2]:07/03/2024 21:28:57 [WARNING|DP=1|PP=0|TP=0|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/03/2024 21:28:57 [WARNING|DP=2|PP=0|TP=1|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/03/2024 21:28:57 [WARNING|DP=3|PP=0|TP=0|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/03/2024 21:28:57 [WARNING|DP=0|PP=0|TP=1|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/03/2024 21:28:57 [WARNING|DP=1|PP=0|TP=1|ip-26-0-174-36]: 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.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/03/2024 21:28:57 [WARNING|DP=3|PP=0|TP=1|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/03/2024 21:28:57 [WARNING|DP=2|PP=0|TP=0|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default1]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default0]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default4]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default6]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default7]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default5]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default2]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default3]:  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
[default0]:07/03/2024 21:29:21 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 3805.28MiB. Peak allocated 13502.50MiB. Peak reserved: 14722.00MiB
[default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default1]:  warnings.warn(
[default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default0]:  warnings.warn(
[default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default4]:  warnings.warn(
[default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default3]:  warnings.warn(
[default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default2]:  warnings.warn(
[default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default5]:  warnings.warn(
[default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default6]:  warnings.warn(
[default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default7]:  warnings.warn(
[default0]:07/03/2024 21:29:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: iteration: 1 / 20 | consumed_tokens: 4.19M | elapsed_time_per_iteration_ms: 30.1K | tokens_per_sec: 140K | tokens_per_sec_per_gpu: 17.4K | global_batch_size: 1.02K | lm_loss: 11.5 | lr: 0.0001 | model_tflops_per_gpu: 158 | hardware_tflops_per_gpu: 158 | grad_norm: 26.4 | cuda_memory_allocated: 5.1G | cuda_max_memory_reserved: 16.5G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.8G | hd_free_memory_tb: 246G
[default0]:07/03/2024 21:29:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 4865.54MiB. Peak allocated 7246.83MiB. Peak reserved: 15782.00MiB
[default0]:07/03/2024 21:29:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 4865.60MiB. Peak allocated 14562.83MiB. Peak reserved: 15782.00MiB
[default0]:07/03/2024 21:29:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: iteration: 2 / 20 | consumed_tokens: 8.39M | elapsed_time_per_iteration_ms: 20.3K | tokens_per_sec: 207K | tokens_per_sec_per_gpu: 25.8K | global_batch_size: 1.02K | lm_loss: 11.5 | lr: 9.53e-05 | model_tflops_per_gpu: 234 | hardware_tflops_per_gpu: 234 | grad_norm: 26.6 | cuda_memory_allocated: 5.1G | cuda_max_memory_reserved: 16.5G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.8G | hd_free_memory_tb: 246G
[default0]:07/03/2024 21:29:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 4865.54MiB. Peak allocated 7246.90MiB. Peak reserved: 15782.00MiB
[default0]:07/03/2024 21:30:08 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 4865.60MiB. Peak allocated 14562.83MiB. Peak reserved: 15782.00MiB
[default0]:07/03/2024 21:30:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: iteration: 3 / 20 | consumed_tokens: 12.6M | elapsed_time_per_iteration_ms: 21.6K | tokens_per_sec: 195K | tokens_per_sec_per_gpu: 24.3K | global_batch_size: 1.02K | lm_loss: 11.5 | lr: 9.05e-05 | model_tflops_per_gpu: 221 | hardware_tflops_per_gpu: 221 | grad_norm: 262 | cuda_memory_allocated: 5.1G | cuda_max_memory_reserved: 16.5G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.8G | hd_free_memory_tb: 246G
[default0]:07/03/2024 21:30:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 4865.54MiB. Peak allocated 7246.90MiB. Peak reserved: 15782.00MiB
[default0]:STAGE:2024-07-03 21:30:09 223115:223115 ActivityProfilerController.cpp:314] Completed Stage: Warm Up
[default0]:07/03/2024 21:30:36 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 4865.60MiB. Peak allocated 14562.83MiB. Peak reserved: 15782.00MiB
[default0]:07/03/2024 21:30:36 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: iteration: 4 / 20 | consumed_tokens: 16.8M | elapsed_time_per_iteration_ms: 27.3K | tokens_per_sec: 154K | tokens_per_sec_per_gpu: 19.2K | global_batch_size: 1.02K | lm_loss: 14.6 | lr: 8.58e-05 | model_tflops_per_gpu: 174 | hardware_tflops_per_gpu: 174 | grad_norm: 29.1 | cuda_memory_allocated: 5.1G | cuda_max_memory_reserved: 16.5G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.8G | hd_free_memory_tb: 246G
[default0]:07/03/2024 21:30:36 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 4865.54MiB. Peak allocated 7246.90MiB. Peak reserved: 15782.00MiB
[default0]:07/03/2024 21:31:03 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: iteration: 5 / 20 | consumed_tokens: 21M | elapsed_time_per_iteration_ms: 27.5K | tokens_per_sec: 153K | tokens_per_sec_per_gpu: 19.1K | global_batch_size: 1.02K | lm_loss: 10.8 | lr: 8.11e-05 | model_tflops_per_gpu: 173 | hardware_tflops_per_gpu: 173 | grad_norm: 31.1
[default0]:07/03/2024 21:31:03 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 4865.54MiB. Peak allocated 14562.83MiB. Peak reserved: 15782.00MiB
[default0]:07/03/2024 21:31:31 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: iteration: 6 / 20 | consumed_tokens: 25.2M | elapsed_time_per_iteration_ms: 27.4K | tokens_per_sec: 153K | tokens_per_sec_per_gpu: 19.1K | global_batch_size: 1.02K | lm_loss: 10.6 | lr: 7.63e-05 | model_tflops_per_gpu: 174 | hardware_tflops_per_gpu: 174 | grad_norm: 27.2
[default0]:STAGE:2024-07-03 21:32:46 223115:223115 ActivityProfilerController.cpp:320] Completed Stage: Collection
[default0]:STAGE:2024-07-03 21:32:54 223115:223115 ActivityProfilerController.cpp:324] Completed Stage: Post Processing
[default1]:[rank1]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=152896, OpType=_REDUCE_SCATTER_BASE, NumelIn=16777216, NumelOut=8388608, Timeout(ms)=600000) ran for 600056 milliseconds before timing out.
[default4]:[rank4]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=165, OpType=ALLREDUCE, NumelIn=554881024, NumelOut=554881024, Timeout(ms)=600000) ran for 600002 milliseconds before timing out.
[default5]:[rank5]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=165, OpType=ALLREDUCE, NumelIn=554881024, NumelOut=554881024, Timeout(ms)=600000) ran for 600036 milliseconds before timing out.
[default3]:[rank3]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=165, OpType=ALLREDUCE, NumelIn=554881024, NumelOut=554881024, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
[default2]:[rank2]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=165, OpType=ALLREDUCE, NumelIn=554881024, NumelOut=554881024, Timeout(ms)=600000) ran for 600055 milliseconds before timing out.
[default2]:[rank2]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=178271, OpType=_ALLGATHER_BASE, NumelIn=8388608, NumelOut=16777216, Timeout(ms)=600000) ran for 600389 milliseconds before timing out.
[default6]:[rank6]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=165, OpType=ALLREDUCE, NumelIn=554881024, NumelOut=554881024, Timeout(ms)=600000) ran for 600027 milliseconds before timing out.
[default4]:[rank4]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=178322, OpType=_REDUCE_SCATTER_BASE, NumelIn=16777216, NumelOut=8388608, Timeout(ms)=600000) ran for 600523 milliseconds before timing out.
[default5]:[rank5]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=178323, OpType=_ALLGATHER_BASE, NumelIn=8388608, NumelOut=16777216, Timeout(ms)=600000) ran for 600558 milliseconds before timing out.
[default3]:[rank3]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=178311, OpType=_ALLGATHER_BASE, NumelIn=8388608, NumelOut=16777216, Timeout(ms)=600000) ran for 600396 milliseconds before timing out.
[default7]:[rank7]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=165, OpType=ALLREDUCE, NumelIn=554881024, NumelOut=554881024, Timeout(ms)=600000) ran for 600075 milliseconds before timing out.
[default6]:[rank6]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=178366, OpType=_REDUCE_SCATTER_BASE, NumelIn=16777216, NumelOut=8388608, Timeout(ms)=600000) ran for 600279 milliseconds before timing out.
[default7]:[rank7]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=178363, OpType=_ALLGATHER_BASE, NumelIn=8388608, NumelOut=16777216, Timeout(ms)=600000) ran for 600320 milliseconds before timing out.
[default1]:[rank1]:[E ProcessGroupNCCL.cpp:1537] [PG 2 Rank 1] Timeout at NCCL work: 152896, last enqueued NCCL work: 153008, last completed NCCL work: 152895.
[default1]:[rank1]:[E ProcessGroupNCCL.cpp:577] [Rank 1] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[default1]:[rank1]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down.
[default1]:[rank1]:[E ProcessGroupNCCL.cpp:1414] [PG 2 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=152896, OpType=_REDUCE_SCATTER_BASE, NumelIn=16777216, NumelOut=8388608, Timeout(ms)=600000) ran for 600056 milliseconds before timing out.
[default1]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default1]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f5f1741a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default1]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f5f186f3c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f5f186f8a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f5f186f9dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #4: <unknown function> + 0xd3e95 (0x7f5f64192e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #5: <unknown function> + 0x8609 (0x7f5f691d9609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #6: clone + 0x43 (0x7f5f68fa4353 in /lib/x86_64-linux-gnu/libc.so.6)
[default1]:
[default1]:terminate called after throwing an instance of 'c10::DistBackendError'
[default1]:  what():  [PG 2 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=152896, OpType=_REDUCE_SCATTER_BASE, NumelIn=16777216, NumelOut=8388608, Timeout(ms)=600000) ran for 600056 milliseconds before timing out.
[default1]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default1]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f5f1741a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default1]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f5f186f3c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f5f186f8a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f5f186f9dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #4: <unknown function> + 0xd3e95 (0x7f5f64192e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #5: <unknown function> + 0x8609 (0x7f5f691d9609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #6: clone + 0x43 (0x7f5f68fa4353 in /lib/x86_64-linux-gnu/libc.so.6)
[default1]:
[default1]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
[default1]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f5f1741a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default1]:frame #1: <unknown function> + 0xe32119 (0x7f5f1837d119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #2: <unknown function> + 0xd3e95 (0x7f5f64192e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #3: <unknown function> + 0x8609 (0x7f5f691d9609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #4: clone + 0x43 (0x7f5f68fa4353 in /lib/x86_64-linux-gnu/libc.so.6)
[default1]:
W0703 21:42:30.109000 140195712452416 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 223115 closing signal SIGTERM
W0703 21:42:30.110000 140195712452416 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 223117 closing signal SIGTERM
W0703 21:42:30.110000 140195712452416 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 223118 closing signal SIGTERM
W0703 21:42:30.110000 140195712452416 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 223119 closing signal SIGTERM
W0703 21:42:30.111000 140195712452416 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 223120 closing signal SIGTERM
W0703 21:42:30.113000 140195712452416 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 223121 closing signal SIGTERM
W0703 21:42:30.114000 140195712452416 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 223122 closing signal SIGTERM
E0703 21:42:33.976000 140195712452416 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: -6) local_rank: 1 (pid: 223116) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
============================================================
/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
------------------------------------------------------------
Failures:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-07-03_21:42:30
  host      : ip-26-0-174-36.ec2.internal
  rank      : 1 (local_rank: 1)
  exitcode  : -6 (pid: 223116)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 223116
============================================================
srun: error: ip-26-0-174-36: task 0: Exited with exit code 1
Consider using `hf_transfer` for faster uploads. This solution comes with some limitations. See https://huggingface.co/docs/huggingface_hub/hf_transfer for more details.

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