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========================
START TIME: Tue Jul  2 15:53:19 UTC 2024
python3 version = Python 3.10.14
========================
The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.
Token is valid (permission: write).
Your token has been saved to /admin/home/ferdinand_mom/.cache/huggingface/token
Login successful
Already on 'bench_cluster'
M	examples/config_tiny_llama.py
M	examples/config_tiny_llama.yaml
M	examples/train_tiny_llama.sh
M	src/nanotron/models/llama.py
M	src/nanotron/trainer.py
Your branch is up to date with 'origin/bench_cluster'.
Job status: RUNNING
W0702 15:53:22.369000 139691473110848 torch/distributed/run.py:757] 
W0702 15:53:22.369000 139691473110848 torch/distributed/run.py:757] *****************************************
W0702 15:53:22.369000 139691473110848 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0702 15:53:22.369000 139691473110848 torch/distributed/run.py:757] *****************************************
W0702 15:53:22.371000 139992463955776 torch/distributed/run.py:757] 
W0702 15:53:22.371000 139992463955776 torch/distributed/run.py:757] *****************************************
W0702 15:53:22.371000 139992463955776 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0702 15:53:22.371000 139992463955776 torch/distributed/run.py:757] *****************************************
[default0]:07/02/2024 15:53:40 [WARNING|DP=0|PP=0|TP=0|ip-26-0-169-132]: [Vocab Size Padding] Padded vocab (size: 50257) with 3 dummy tokens (new size: 50260)
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: Config:
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: Config(general=GeneralArgs(project='bench_cluster',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                            run='%date_%jobid',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                            seed=42,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                            step=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                            consumed_train_samples=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                            benchmark_csv_path=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                            ignore_sanity_checks=True),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:        parallelism=ParallelismArgs(dp=2,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                    pp=2,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                    tp=4,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                    pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7f8097eac910>,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                    tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                    tp_linear_async_communication=False,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                    expert_parallel_size=1),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:        model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 eos_token_id=2,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 hidden_act='silu',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 hidden_size=2048,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 initializer_range=0.02,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 intermediate_size=4096,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 is_llama_config=True,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 max_position_embeddings=4096,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 num_attention_heads=32,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 num_hidden_layers=24,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 num_key_value_heads=32,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 pad_token_id=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 pretraining_tp=1,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 rms_norm_eps=1e-05,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 rope_scaling=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 rope_theta=10000.0,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 tie_word_embeddings=True,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 use_cache=True,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                 vocab_size=50260),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                        init_method=RandomInit(std=0.025),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                        dtype=torch.bfloat16,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                        make_vocab_size_divisible_by=1,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                        ddp_bucket_cap_mb=25),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:        tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                tokenizer_revision=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                tokenizer_max_length=None),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:        checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                    checkpoint_interval=100000,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                    save_initial_state=False,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                    resume_checkpoint_path=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                    checkpoints_path_is_shared_file_system=False),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:        logging=LoggingArgs(log_level='info',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                            log_level_replica='info',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                            iteration_step_info_interval=1),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:        tokens=TokensArgs(sequence_length=4096,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                          train_steps=20,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                          micro_batch_size=1,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                          batch_accumulation_per_replica=512,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                          val_check_interval=-1,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                          limit_val_batches=0,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                          limit_test_batches=0),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:        optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                     adam_beta1=0.9,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                     adam_beta2=0.95,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                     torch_adam_is_fused=True,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                     name='adamW'),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                zero_stage=1,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                weight_decay=0.01,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                clip_grad=1.0,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                accumulate_grad_in_fp32=True,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                        lr_warmup_steps=1,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                        lr_warmup_style='linear',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                        lr_decay_style='linear',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                        lr_decay_steps=19,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                        lr_decay_starting_step=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                        min_decay_lr=1e-05)),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:        data_stages=[DatasetStageArgs(name='Training Stage',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                      start_training_step=1,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                      data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                                 hf_dataset_splits='train',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                                 hf_dataset_config_name=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                                 dataset_processing_num_proc_per_process=64,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                                 dataset_overwrite_cache=False,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                                                 text_column_name='text'),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                    seed=42,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:                                                    num_loading_workers=32))],
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:        profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-2_tp-4_pp-2_mbz-1')),
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:        lighteval=None)
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: Model Config:
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: LlamaConfig(bos_token_id=1,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             eos_token_id=2,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             hidden_act='silu',
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             hidden_size=2048,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             initializer_range=0.02,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             intermediate_size=4096,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             is_llama_config=True,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             max_position_embeddings=4096,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             num_attention_heads=32,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             num_hidden_layers=24,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             num_key_value_heads=32,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             pad_token_id=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             pretraining_tp=1,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             rms_norm_eps=1e-05,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             rope_scaling=None,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             rope_theta=10000.0,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             tie_word_embeddings=True,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             use_cache=True,
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:             vocab_size=50260)
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: Building model..
[default0]:07/02/2024 15:53:40 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: Setting PP block ranks...
[default1]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=1|ip-26-0-169-132]: Local number of parameters: 173M (329.19MiB)
[default1]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=1|ip-26-0-169-132]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
[default1]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=1|ip-26-0-169-132]: No checkpoint path provided.
[default2]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=2|ip-26-0-169-132]: Local number of parameters: 173M (329.19MiB)
[default2]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=2|ip-26-0-169-132]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
[default2]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=2|ip-26-0-169-132]: No checkpoint path provided.
[default0]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: Total number of parameters: 1.21G (2313.42MiB)
[default0]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: Local number of parameters: 173M (329.19MiB)
[default0]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
[default0]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: No checkpoint path provided.
[default0]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: Parametrizing model parameters using StandardParametrizator
[default3]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=3|ip-26-0-169-132]: Local number of parameters: 173M (329.19MiB)
[default3]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=3|ip-26-0-169-132]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
[default3]:07/02/2024 15:53:54 [INFO|DP=0|PP=0|TP=3|ip-26-0-169-132]: No checkpoint path provided.
[default0]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=0|ip-26-0-175-132]: Local number of parameters: 131M (249.16MiB)
[default0]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=0|ip-26-0-175-132]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
[default0]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=0|ip-26-0-175-132]: No checkpoint path provided.
[default2]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=2|ip-26-0-175-132]: Local number of parameters: 131M (249.16MiB)
[default2]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=2|ip-26-0-175-132]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
[default2]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=2|ip-26-0-175-132]: No checkpoint path provided.
[default1]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=1|ip-26-0-175-132]: Local number of parameters: 131M (249.16MiB)
[default3]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=3|ip-26-0-175-132]: Local number of parameters: 131M (249.16MiB)
[default3]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=3|ip-26-0-175-132]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
[default1]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=1|ip-26-0-175-132]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
[default1]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=1|ip-26-0-175-132]: No checkpoint path provided.
[default3]:07/02/2024 15:53:54 [INFO|DP=0|PP=1|TP=3|ip-26-0-175-132]: No checkpoint path provided.
[default4]:07/02/2024 15:53:54 [INFO|DP=1|PP=0|TP=0|ip-26-0-169-132]: No checkpoint path provided.
[default7]:07/02/2024 15:53:54 [INFO|DP=1|PP=0|TP=3|ip-26-0-169-132]: No checkpoint path provided.
[default5]:07/02/2024 15:53:54 [INFO|DP=1|PP=0|TP=1|ip-26-0-169-132]: No checkpoint path provided.
[default6]:07/02/2024 15:53:54 [INFO|DP=1|PP=0|TP=2|ip-26-0-169-132]: No checkpoint path provided.
[default7]:07/02/2024 15:53:55 [INFO|DP=1|PP=1|TP=3|ip-26-0-175-132]: No checkpoint path provided.
[default4]:07/02/2024 15:53:55 [INFO|DP=1|PP=1|TP=0|ip-26-0-175-132]: No checkpoint path provided.
[default6]:07/02/2024 15:53:55 [INFO|DP=1|PP=1|TP=2|ip-26-0-175-132]: No checkpoint path provided.
[default5]:07/02/2024 15:53:55 [INFO|DP=1|PP=1|TP=1|ip-26-0-175-132]: No checkpoint path provided.
[default0]:07/02/2024 15:53:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: [Optimizer Building] Using LearningRateForSP as learning rate
[default0]:07/02/2024 15:53:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: [ZeRO sharding] Size of optimizer params per rank:
[default0]:07/02/2024 15:53:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: [ZeRO sharding] DP Rank 0 has 86.3M out of 173M (50.00%) params' optimizer states
[default0]:07/02/2024 15:53:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: [ZeRO sharding] DP Rank 1 has 86.3M out of 173M (50.00%) params' optimizer states
[default0]:07/02/2024 15:53:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
[default0]:07/02/2024 15:53:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: Using `datasets` library
[default0]:07/02/2024 15:53:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: 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]:07/02/2024 15:53:58 [WARNING|DP=0|PP=0|TP=0|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/02/2024 15:53:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: [Training Plan] There are 1 training stages 
[default0]:07/02/2024 15:53:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: [Stage Training Stage] start from step 1 
[default0]:07/02/2024 15:53:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: 
[default0]:07/02/2024 15:53:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: [Start training] datetime: 2024-07-02 15:53:59.263973 | mbs: 1 | grad_accum: 512 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
[default0]:07/02/2024 15:53:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
[default0]:07/02/2024 15:53:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:  Memory usage: 1332.51MiB. Peak allocated 1332.51MiB. Peak reserved: 1338.00MiB
[default1]:07/02/2024 15:53:59 [WARNING|DP=0|PP=0|TP=1|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/02/2024 15:53:59 [WARNING|DP=0|PP=0|TP=2|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/02/2024 15:53:59 [WARNING|DP=1|PP=0|TP=0|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/02/2024 15:53:59 [WARNING|DP=1|PP=0|TP=3|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/02/2024 15:53:59 [WARNING|DP=1|PP=0|TP=1|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/02/2024 15:53:59 [WARNING|DP=0|PP=0|TP=3|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/02/2024 15:53:59 [WARNING|DP=1|PP=0|TP=2|ip-26-0-169-132]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/02/2024 15:53:59 [WARNING|DP=1|PP=1|TP=3|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/02/2024 15:53:59 [WARNING|DP=1|PP=1|TP=0|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/02/2024 15:53:59 [WARNING|DP=0|PP=1|TP=2|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/02/2024 15:53:59 [WARNING|DP=0|PP=1|TP=0|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/02/2024 15:53:59 [WARNING|DP=0|PP=1|TP=1|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/02/2024 15:53:59 [WARNING|DP=0|PP=1|TP=3|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/02/2024 15:53:59 [WARNING|DP=1|PP=1|TP=2|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default6]: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.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/02/2024 15:53:59 [WARNING|DP=1|PP=1|TP=1|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[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
[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
[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
[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
[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
[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
[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
[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
[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
[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
[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
[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
[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
[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(
[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(
[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]:07/02/2024 15:55:03 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:  Memory usage: 1403.54MiB. Peak allocated 4317.13MiB. Peak reserved: 4390.00MiB
[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(
[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(
[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(
[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(
[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(
[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(
[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(
[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(
[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(
[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(
[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(
[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(
[default0]:07/02/2024 15:55:25 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:  Memory usage: 2061.97MiB. Peak allocated 2885.75MiB. Peak reserved: 5052.00MiB
[default0]:07/02/2024 15:55:25 [INFO|DP=0|PP=1|TP=0|ip-26-0-175-132]: iteration: 1 / 20 | consumed_tokens: 4.19M | elapsed_time_per_iteration_ms: 85.3K | tokens_per_sec: 49.2K | tokens_per_sec_per_gpu: 3.07K | global_batch_size: 1.02K | lm_loss: 11.1 | lr: 0.0001 | model_tflops_per_gpu: 27.9 | hardware_tflops_per_gpu: 27.9 | grad_norm: 15 | cuda_memory_allocated: 1.65G | cuda_max_memory_reserved: 3.18G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.5G | hd_free_memory_tb: 247G
[default0]:07/02/2024 15:56:13 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:  Memory usage: 2061.97MiB. Peak allocated 4785.80MiB. Peak reserved: 5052.00MiB
[default0]:07/02/2024 15:56:23 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:  Memory usage: 2061.97MiB. Peak allocated 2885.75MiB. Peak reserved: 5052.00MiB
[default0]:07/02/2024 15:56:23 [INFO|DP=0|PP=1|TP=0|ip-26-0-175-132]: iteration: 2 / 20 | consumed_tokens: 8.39M | elapsed_time_per_iteration_ms: 58.3K | tokens_per_sec: 71.9K | tokens_per_sec_per_gpu: 4.49K | global_batch_size: 1.02K | lm_loss: 11.1 | lr: 9.53e-05 | model_tflops_per_gpu: 40.8 | hardware_tflops_per_gpu: 40.8 | grad_norm: 15.1 | cuda_memory_allocated: 1.65G | cuda_max_memory_reserved: 3.18G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.5G | hd_free_memory_tb: 247G
[default0]:07/02/2024 15:57:12 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:  Memory usage: 2061.97MiB. Peak allocated 4785.80MiB. Peak reserved: 5052.00MiB
[default0]:07/02/2024 15:57:21 [INFO|DP=0|PP=1|TP=0|ip-26-0-175-132]: iteration: 3 / 20 | consumed_tokens: 12.6M | elapsed_time_per_iteration_ms: 57.9K | tokens_per_sec: 72.5K | tokens_per_sec_per_gpu: 4.53K | global_batch_size: 1.02K | lm_loss: 11.4 | lr: 9.05e-05 | model_tflops_per_gpu: 41.1 | hardware_tflops_per_gpu: 41.1 | grad_norm: 106 | cuda_memory_allocated: 1.65G | cuda_max_memory_reserved: 3.18G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.5G | hd_free_memory_tb: 247G
[default0]:07/02/2024 15:57:21 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:  Memory usage: 2061.97MiB. Peak allocated 2885.75MiB. Peak reserved: 5052.00MiB
[default0]:STAGE:2024-07-02 15:57:21 2303216:2303216 ActivityProfilerController.cpp:314] Completed Stage: Warm Up
[default0]:07/02/2024 15:58:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:  Memory usage: 2061.97MiB. Peak allocated 4785.80MiB. Peak reserved: 5052.00MiB
[default0]:07/02/2024 15:58:28 [INFO|DP=0|PP=1|TP=0|ip-26-0-175-132]: iteration: 4 / 20 | consumed_tokens: 16.8M | elapsed_time_per_iteration_ms: 67.2K | tokens_per_sec: 62.4K | tokens_per_sec_per_gpu: 3.9K | global_batch_size: 1.02K | lm_loss: 11.7 | lr: 8.58e-05 | model_tflops_per_gpu: 35.4 | hardware_tflops_per_gpu: 35.4 | grad_norm: 24.5 | cuda_memory_allocated: 1.65G | cuda_max_memory_reserved: 3.18G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.5G | hd_free_memory_tb: 247G
[default0]:07/02/2024 15:58:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:  Memory usage: 2061.97MiB. Peak allocated 2885.75MiB. Peak reserved: 5052.00MiB
[default0]:07/02/2024 15:59:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-132]:  Memory usage: 2061.97MiB. Peak allocated 4785.80MiB. Peak reserved: 5052.00MiB
[default0]:07/02/2024 15:59:37 [INFO|DP=0|PP=1|TP=0|ip-26-0-175-132]: iteration: 5 / 20 | consumed_tokens: 21M | elapsed_time_per_iteration_ms: 68.8K | tokens_per_sec: 61K | tokens_per_sec_per_gpu: 3.81K | global_batch_size: 1.02K | lm_loss: 10 | lr: 8.11e-05 | model_tflops_per_gpu: 34.6 | hardware_tflops_per_gpu: 34.6 | grad_norm: 11
[default0]:07/02/2024 16:00:45 [INFO|DP=0|PP=1|TP=0|ip-26-0-175-132]: iteration: 6 / 20 | consumed_tokens: 25.2M | elapsed_time_per_iteration_ms: 68.1K | tokens_per_sec: 61.6K | tokens_per_sec_per_gpu: 3.85K | global_batch_size: 1.02K | lm_loss: 9.46 | lr: 7.63e-05 | model_tflops_per_gpu: 34.9 | hardware_tflops_per_gpu: 34.9 | grad_norm: 7.21
[default0]:STAGE:2024-07-02 16:04:04 2303216:2303216 ActivityProfilerController.cpp:320] Completed Stage: Collection
[default0]:STAGE:2024-07-02 16:04:36 2303216:2303216 ActivityProfilerController.cpp:324] Completed Stage: Post Processing
[default3]:[rank11]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
[default1]:[rank9]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600016 milliseconds before timing out.
[default2]:[rank2]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=350245, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600003 milliseconds before timing out.
[default1]:[rank1]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=350245, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600022 milliseconds before timing out.
[default3]:[rank3]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=350245, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600092 milliseconds before timing out.
[default2]:[rank10]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600094 milliseconds before timing out.
[default0]:[rank8]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600089 milliseconds before timing out.
[default0]:[rank8]: Traceback (most recent call last):
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default0]:[rank8]:     trainer.train(dataloader)
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default0]:[rank8]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default0]:[rank8]:     outputs = self.pipeline_engine.train_batch_iter(
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
[default0]:[rank8]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default0]:[rank8]:     output = model(**micro_batch)
[default0]:[rank8]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default0]:[rank8]:     return self._call_impl(*args, **kwargs)
[default0]:[rank8]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default0]:[rank8]:     return forward_call(*args, **kwargs)
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default0]:[rank8]:     sharded_logits = self.model(
[default0]:[rank8]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default0]:[rank8]:     return self._call_impl(*args, **kwargs)
[default0]:[rank8]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default0]:[rank8]:     return forward_call(*args, **kwargs)
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default0]:[rank8]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default0]:[rank8]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default0]:[rank8]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default0]:[rank8]:     return self._call_impl(*args, **kwargs)
[default0]:[rank8]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default0]:[rank8]:     return forward_call(*args, **kwargs)
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default0]:[rank8]:     new_kwargs[name] = recv_from_pipeline_state_buffer(
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default0]:[rank8]:     pipeline_state.run_communication()
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default0]:[rank8]:     recv_activation_tensor = recv_activation()
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default0]:[rank8]:     return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default0]:[rank8]:     buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default0]:[rank8]:     meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default0]:[rank8]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta
[default0]:[rank8]:     dist.recv(
[default0]:[rank8]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper
[default0]:[rank8]:     return func(*args, **kwargs)
[default0]:[rank8]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv
[default0]:[rank8]:     pg.recv([tensor], group_src_rank, tag).wait()
[default0]:[rank8]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. 
[default3]:[rank11]: Traceback (most recent call last):
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default3]:[rank11]:     trainer.train(dataloader)
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default3]:[rank11]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default3]:[rank11]:     outputs = self.pipeline_engine.train_batch_iter(
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
[default3]:[rank11]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default3]:[rank11]:     output = model(**micro_batch)
[default3]:[rank11]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default3]:[rank11]:     return self._call_impl(*args, **kwargs)
[default3]:[rank11]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default3]:[rank11]:     return forward_call(*args, **kwargs)
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default3]:[rank11]:     sharded_logits = self.model(
[default3]:[rank11]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default3]:[rank11]:     return self._call_impl(*args, **kwargs)
[default3]:[rank11]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default3]:[rank11]:     return forward_call(*args, **kwargs)
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default3]:[rank11]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default3]:[rank11]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default3]:[rank11]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default3]:[rank11]:     return self._call_impl(*args, **kwargs)
[default3]:[rank11]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default3]:[rank11]:     return forward_call(*args, **kwargs)
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default3]:[rank11]:     new_kwargs[name] = recv_from_pipeline_state_buffer(
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default3]:[rank11]:     pipeline_state.run_communication()
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default3]:[rank11]:     recv_activation_tensor = recv_activation()
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default3]:[rank11]:     return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default3]:[rank11]:     buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default3]:[rank11]:     meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default3]:[rank11]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta
[default3]:[rank11]:     dist.recv(
[default3]:[rank11]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper
[default3]:[rank11]:     return func(*args, **kwargs)
[default3]:[rank11]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv
[default3]:[rank11]:     pg.recv([tensor], group_src_rank, tag).wait()
[default3]:[rank11]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. 
[default0]:[rank8]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 27658, last enqueued NCCL work: 27658, last completed NCCL work: 27657.
[default0]:[rank8]:[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.
[default0]:[rank8]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down.
[default0]:[rank8]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600089 milliseconds before timing out.
[default0]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default0]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fbdb1108897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default0]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7fbdb23e1c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default0]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7fbdb23e6a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default0]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7fbdb23e7dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default0]:frame #4: <unknown function> + 0xd3e95 (0x7fbdfde80e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default0]:frame #5: <unknown function> + 0x8609 (0x7fbe02ec7609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default0]:frame #6: clone + 0x43 (0x7fbe02c92353 in /lib/x86_64-linux-gnu/libc.so.6)
[default0]:
[default0]:terminate called after throwing an instance of 'c10::DistBackendError'
[default0]:  what():  [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600089 milliseconds before timing out.
[default0]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default0]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fbdb1108897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default0]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7fbdb23e1c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default0]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7fbdb23e6a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default0]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7fbdb23e7dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default0]:frame #4: <unknown function> + 0xd3e95 (0x7fbdfde80e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default0]:frame #5: <unknown function> + 0x8609 (0x7fbe02ec7609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default0]:frame #6: clone + 0x43 (0x7fbe02c92353 in /lib/x86_64-linux-gnu/libc.so.6)
[default0]:
[default0]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
[default0]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fbdb1108897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default0]:frame #1: <unknown function> + 0xe32119 (0x7fbdb206b119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default0]:frame #2: <unknown function> + 0xd3e95 (0x7fbdfde80e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default0]:frame #3: <unknown function> + 0x8609 (0x7fbe02ec7609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default0]:frame #4: clone + 0x43 (0x7fbe02c92353 in /lib/x86_64-linux-gnu/libc.so.6)
[default0]:
[default1]:[rank9]: Traceback (most recent call last):
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default1]:[rank9]:     trainer.train(dataloader)
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default1]:[rank9]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default1]:[rank9]:     outputs = self.pipeline_engine.train_batch_iter(
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
[default1]:[rank9]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default1]:[rank9]:     output = model(**micro_batch)
[default1]:[rank9]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default1]:[rank9]:     return self._call_impl(*args, **kwargs)
[default1]:[rank9]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default1]:[rank9]:     return forward_call(*args, **kwargs)
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default1]:[rank9]:     sharded_logits = self.model(
[default1]:[rank9]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default1]:[rank9]:     return self._call_impl(*args, **kwargs)
[default1]:[rank9]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default1]:[rank9]:     return forward_call(*args, **kwargs)
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default1]:[rank9]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default1]:[rank9]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default1]:[rank9]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default1]:[rank9]:     return self._call_impl(*args, **kwargs)
[default1]:[rank9]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default1]:[rank9]:     return forward_call(*args, **kwargs)
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default1]:[rank9]:     new_kwargs[name] = recv_from_pipeline_state_buffer(
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default1]:[rank9]:     pipeline_state.run_communication()
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default1]:[rank9]:     recv_activation_tensor = recv_activation()
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default1]:[rank9]:     return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default1]:[rank9]:     buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default1]:[rank9]:     meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default1]:[rank9]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta
[default1]:[rank9]:     dist.recv(
[default1]:[rank9]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper
[default1]:[rank9]:     return func(*args, **kwargs)
[default1]:[rank9]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv
[default1]:[rank9]:     pg.recv([tensor], group_src_rank, tag).wait()
[default1]:[rank9]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. 
[default3]:[rank11]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 27658, last enqueued NCCL work: 27658, last completed NCCL work: 27657.
[default3]:[rank11]:[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.
[default3]:[rank11]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down.
[default3]:[rank11]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
[default3]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default3]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f09beeec897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default3]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f09c01c5c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f09c01caa80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f09c01cbdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #4: <unknown function> + 0xd3e95 (0x7f0a0bc64e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default3]:frame #5: <unknown function> + 0x8609 (0x7f0a10cab609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default3]:frame #6: clone + 0x43 (0x7f0a10a76353 in /lib/x86_64-linux-gnu/libc.so.6)
[default3]:
[default3]:terminate called after throwing an instance of 'c10::DistBackendError'
[default3]:  what():  [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
[default3]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default3]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f09beeec897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default3]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f09c01c5c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f09c01caa80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f09c01cbdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #4: <unknown function> + 0xd3e95 (0x7f0a0bc64e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default3]:frame #5: <unknown function> + 0x8609 (0x7f0a10cab609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default3]:frame #6: clone + 0x43 (0x7f0a10a76353 in /lib/x86_64-linux-gnu/libc.so.6)
[default3]:
[default3]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
[default3]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f09beeec897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default3]:frame #1: <unknown function> + 0xe32119 (0x7f09bfe4f119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #2: <unknown function> + 0xd3e95 (0x7f0a0bc64e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default3]:frame #3: <unknown function> + 0x8609 (0x7f0a10cab609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default3]:frame #4: clone + 0x43 (0x7f0a10a76353 in /lib/x86_64-linux-gnu/libc.so.6)
[default3]:
[default2]:[rank10]: Traceback (most recent call last):
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default2]:[rank10]:     trainer.train(dataloader)
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default2]:[rank10]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default2]:[rank10]:     outputs = self.pipeline_engine.train_batch_iter(
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
[default2]:[rank10]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default2]:[rank10]:     output = model(**micro_batch)
[default2]:[rank10]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default2]:[rank10]:     return self._call_impl(*args, **kwargs)
[default2]:[rank10]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default2]:[rank10]:     return forward_call(*args, **kwargs)
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default2]:[rank10]:     sharded_logits = self.model(
[default2]:[rank10]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default2]:[rank10]:     return self._call_impl(*args, **kwargs)
[default2]:[rank10]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default2]:[rank10]:     return forward_call(*args, **kwargs)
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default2]:[rank10]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default2]:[rank10]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default2]:[rank10]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default2]:[rank10]:     return self._call_impl(*args, **kwargs)
[default2]:[rank10]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default2]:[rank10]:     return forward_call(*args, **kwargs)
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default2]:[rank10]:     new_kwargs[name] = recv_from_pipeline_state_buffer(
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default2]:[rank10]:     pipeline_state.run_communication()
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default2]:[rank10]:     recv_activation_tensor = recv_activation()
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default2]:[rank10]:     return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default2]:[rank10]:     buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default2]:[rank10]:     meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default2]:[rank10]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta
[default2]:[rank10]:     dist.recv(
[default2]:[rank10]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper
[default2]:[rank10]:     return func(*args, **kwargs)
[default2]:[rank10]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv
[default2]:[rank10]:     pg.recv([tensor], group_src_rank, tag).wait()
[default2]:[rank10]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. 
[default1]:[rank9]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 27658, last enqueued NCCL work: 27658, last completed NCCL work: 27657.
[default1]:[rank9]:[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]:[rank9]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down.
[default1]:[rank9]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600016 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 (0x7f5d73c62897 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 (0x7f5d74f3bc62 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 (0x7f5d74f40a80 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 (0x7f5d74f41dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #4: <unknown function> + 0xd3e95 (0x7f5dc09dae95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #5: <unknown function> + 0x8609 (0x7f5dc5a21609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #6: clone + 0x43 (0x7f5dc57ec353 in /lib/x86_64-linux-gnu/libc.so.6)
[default1]:
[default1]:terminate called after throwing an instance of 'c10::DistBackendError'
[default1]:  what():  [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600016 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 (0x7f5d73c62897 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 (0x7f5d74f3bc62 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 (0x7f5d74f40a80 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 (0x7f5d74f41dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #4: <unknown function> + 0xd3e95 (0x7f5dc09dae95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #5: <unknown function> + 0x8609 (0x7f5dc5a21609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #6: clone + 0x43 (0x7f5dc57ec353 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 (0x7f5d73c62897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default1]:frame #1: <unknown function> + 0xe32119 (0x7f5d74bc5119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #2: <unknown function> + 0xd3e95 (0x7f5dc09dae95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #3: <unknown function> + 0x8609 (0x7f5dc5a21609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #4: clone + 0x43 (0x7f5dc57ec353 in /lib/x86_64-linux-gnu/libc.so.6)
[default1]:
[default2]:[rank10]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 27658, last enqueued NCCL work: 27658, last completed NCCL work: 27657.
[default2]:[rank10]:[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.
[default2]:[rank10]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down.
[default2]:[rank10]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600094 milliseconds before timing out.
[default2]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default2]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f9fb28c7897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default2]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f9fb3ba0c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f9fb3ba5a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f9fb3ba6dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #4: <unknown function> + 0xd3e95 (0x7f9fff63fe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default2]:frame #5: <unknown function> + 0x8609 (0x7fa004686609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default2]:frame #6: clone + 0x43 (0x7fa004451353 in /lib/x86_64-linux-gnu/libc.so.6)
[default2]:
[default2]:terminate called after throwing an instance of 'c10::DistBackendError'
[default2]:  what():  [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27658, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600094 milliseconds before timing out.
[default2]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default2]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f9fb28c7897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default2]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f9fb3ba0c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f9fb3ba5a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f9fb3ba6dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #4: <unknown function> + 0xd3e95 (0x7f9fff63fe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default2]:frame #5: <unknown function> + 0x8609 (0x7fa004686609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default2]:frame #6: clone + 0x43 (0x7fa004451353 in /lib/x86_64-linux-gnu/libc.so.6)
[default2]:
[default2]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
[default2]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f9fb28c7897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default2]:frame #1: <unknown function> + 0xe32119 (0x7f9fb382a119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #2: <unknown function> + 0xd3e95 (0x7f9fff63fe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default2]:frame #3: <unknown function> + 0x8609 (0x7fa004686609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default2]:frame #4: clone + 0x43 (0x7fa004451353 in /lib/x86_64-linux-gnu/libc.so.6)
[default2]:
W0702 16:10:49.472000 139992463955776 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 141705 closing signal SIGTERM
W0702 16:10:49.477000 139992463955776 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 141706 closing signal SIGTERM
W0702 16:10:49.484000 139992463955776 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 141707 closing signal SIGTERM
W0702 16:10:49.487000 139992463955776 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 141708 closing signal SIGTERM
E0702 16:10:51.454000 139992463955776 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: -6) local_rank: 0 (pid: 141701) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
============================================================
/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
------------------------------------------------------------
Failures:
[1]:
  time      : 2024-07-02_16:10:49
  host      : ip-26-0-175-132.ec2.internal
  rank      : 9 (local_rank: 1)
  exitcode  : -6 (pid: 141702)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 141702
[2]:
  time      : 2024-07-02_16:10:49
  host      : ip-26-0-175-132.ec2.internal
  rank      : 10 (local_rank: 2)
  exitcode  : -6 (pid: 141703)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 141703
[3]:
  time      : 2024-07-02_16:10:49
  host      : ip-26-0-175-132.ec2.internal
  rank      : 11 (local_rank: 3)
  exitcode  : -6 (pid: 141704)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 141704
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-07-02_16:10:49
  host      : ip-26-0-175-132.ec2.internal
  rank      : 8 (local_rank: 0)
  exitcode  : -6 (pid: 141701)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 141701
============================================================
srun: error: ip-26-0-175-132: task 1: Exited with exit code 1
[default3]:[rank3]: Traceback (most recent call last):
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default3]:[rank3]:     trainer.train(dataloader)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default3]:[rank3]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default3]:[rank3]:     outputs = self.pipeline_engine.train_batch_iter(
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 258, in train_batch_iter
[default3]:[rank3]:     send_activation()
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 22, in __call__
[default3]:[rank3]:     self.p2p.send_tensors([self.activation], to_rank=self.to_rank)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 348, in send_tensors
[default3]:[rank3]:     futures = self.isend_tensors(tensors=tensors, to_rank=to_rank, tag=tag)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 306, in isend_tensors
[default3]:[rank3]:     dist.isend(
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1809, in isend
[default3]:[rank3]:     return pg.send([tensor], dst, tag)
[default3]:[rank3]: RuntimeError: Unconvertible NCCL type
[default2]:[rank2]: Traceback (most recent call last):
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default2]:[rank2]:     trainer.train(dataloader)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default2]:[rank2]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default2]:[rank2]:     outputs = self.pipeline_engine.train_batch_iter(
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 258, in train_batch_iter
[default2]:[rank2]:     send_activation()
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 22, in __call__
[default2]:[rank2]:     self.p2p.send_tensors([self.activation], to_rank=self.to_rank)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 348, in send_tensors
[default2]:[rank2]:     futures = self.isend_tensors(tensors=tensors, to_rank=to_rank, tag=tag)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 306, in isend_tensors
[default2]:[rank2]:     dist.isend(
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1809, in isend
[default2]:[rank2]:     return pg.send([tensor], dst, tag)
[default2]:[rank2]: RuntimeError: Unconvertible NCCL type
[default1]:[rank1]: Traceback (most recent call last):
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default1]:[rank1]:     trainer.train(dataloader)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default1]:[rank1]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default1]:[rank1]:     outputs = self.pipeline_engine.train_batch_iter(
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 258, in train_batch_iter
[default1]:[rank1]:     send_activation()
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 22, in __call__
[default1]:[rank1]:     self.p2p.send_tensors([self.activation], to_rank=self.to_rank)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 348, in send_tensors
[default1]:[rank1]:     futures = self.isend_tensors(tensors=tensors, to_rank=to_rank, tag=tag)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 306, in isend_tensors
[default1]:[rank1]:     dist.isend(
[default1]:[rank1]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1809, in isend
[default1]:[rank1]:     return pg.send([tensor], dst, tag)
[default1]:[rank1]: RuntimeError: Unconvertible NCCL type
[default2]:[rank2]:[E ProcessGroupNCCL.cpp:1537] [PG 2 Rank 2] Timeout at NCCL work: 350245, last enqueued NCCL work: 350301, last completed NCCL work: 350244.
[default2]:[rank2]:[E ProcessGroupNCCL.cpp:577] [Rank 2] 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.
[default2]:[rank2]:[E ProcessGroupNCCL.cpp:583] [Rank 2] To avoid data inconsistency, we are taking the entire process down.
[default2]:[rank2]:[E ProcessGroupNCCL.cpp:1414] [PG 2 Rank 2] Process group watchdog thread terminated with exception: [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=350245, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600003 milliseconds before timing out.
[default2]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default2]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fe7ea0ac897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default2]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7fe7eb385c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7fe7eb38aa80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7fe7eb38bdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #4: <unknown function> + 0xd3e95 (0x7fe836e24e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default2]:frame #5: <unknown function> + 0x8609 (0x7fe83be6b609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default2]:frame #6: clone + 0x43 (0x7fe83bc36353 in /lib/x86_64-linux-gnu/libc.so.6)
[default2]:
[default2]:terminate called after throwing an instance of 'c10::DistBackendError'
[default2]:  what():  [PG 2 Rank 2] Process group watchdog thread terminated with exception: [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=350245, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600003 milliseconds before timing out.
[default2]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default2]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fe7ea0ac897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default2]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7fe7eb385c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7fe7eb38aa80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7fe7eb38bdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #4: <unknown function> + 0xd3e95 (0x7fe836e24e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default2]:frame #5: <unknown function> + 0x8609 (0x7fe83be6b609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default2]:frame #6: clone + 0x43 (0x7fe83bc36353 in /lib/x86_64-linux-gnu/libc.so.6)
[default2]:
[default2]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
[default2]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fe7ea0ac897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default2]:frame #1: <unknown function> + 0xe32119 (0x7fe7eb00f119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default2]:frame #2: <unknown function> + 0xd3e95 (0x7fe836e24e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default2]:frame #3: <unknown function> + 0x8609 (0x7fe83be6b609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default2]:frame #4: clone + 0x43 (0x7fe83bc36353 in /lib/x86_64-linux-gnu/libc.so.6)
[default2]:
[default1]:[rank1]:[E ProcessGroupNCCL.cpp:1537] [PG 2 Rank 1] Timeout at NCCL work: 350245, last enqueued NCCL work: 350301, last completed NCCL work: 350244.
[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=350245, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600022 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 (0x7f312f6ee897 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 (0x7f31309c7c62 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 (0x7f31309cca80 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 (0x7f31309cddcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #4: <unknown function> + 0xd3e95 (0x7f317c466e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #5: <unknown function> + 0x8609 (0x7f31814ad609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #6: clone + 0x43 (0x7f3181278353 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=350245, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600022 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 (0x7f312f6ee897 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 (0x7f31309c7c62 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 (0x7f31309cca80 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 (0x7f31309cddcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #4: <unknown function> + 0xd3e95 (0x7f317c466e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #5: <unknown function> + 0x8609 (0x7f31814ad609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #6: clone + 0x43 (0x7f3181278353 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 (0x7f312f6ee897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default1]:frame #1: <unknown function> + 0xe32119 (0x7f3130651119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #2: <unknown function> + 0xd3e95 (0x7f317c466e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #3: <unknown function> + 0x8609 (0x7f31814ad609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #4: clone + 0x43 (0x7f3181278353 in /lib/x86_64-linux-gnu/libc.so.6)
[default1]:
[default3]:[rank3]:[E ProcessGroupNCCL.cpp:1537] [PG 2 Rank 3] Timeout at NCCL work: 350245, last enqueued NCCL work: 350301, last completed NCCL work: 350244.
[default3]:[rank3]:[E ProcessGroupNCCL.cpp:577] [Rank 3] 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.
[default3]:[rank3]:[E ProcessGroupNCCL.cpp:583] [Rank 3] To avoid data inconsistency, we are taking the entire process down.
[default3]:[rank3]:[E ProcessGroupNCCL.cpp:1414] [PG 2 Rank 3] Process group watchdog thread terminated with exception: [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=350245, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600092 milliseconds before timing out.
[default3]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default3]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fd2e5cae897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default3]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7fd2e6f87c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7fd2e6f8ca80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7fd2e6f8ddcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #4: <unknown function> + 0xd3e95 (0x7fd332a26e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default3]:frame #5: <unknown function> + 0x8609 (0x7fd337a6d609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default3]:frame #6: clone + 0x43 (0x7fd337838353 in /lib/x86_64-linux-gnu/libc.so.6)
[default3]:
[default3]:terminate called after throwing an instance of 'c10::DistBackendError'
[default3]:  what():  [PG 2 Rank 3] Process group watchdog thread terminated with exception: [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=350245, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600092 milliseconds before timing out.
[default3]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default3]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fd2e5cae897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default3]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7fd2e6f87c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7fd2e6f8ca80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7fd2e6f8ddcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #4: <unknown function> + 0xd3e95 (0x7fd332a26e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default3]:frame #5: <unknown function> + 0x8609 (0x7fd337a6d609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default3]:frame #6: clone + 0x43 (0x7fd337838353 in /lib/x86_64-linux-gnu/libc.so.6)
[default3]:
[default3]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
[default3]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fd2e5cae897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default3]:frame #1: <unknown function> + 0xe32119 (0x7fd2e6c11119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default3]:frame #2: <unknown function> + 0xd3e95 (0x7fd332a26e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default3]:frame #3: <unknown function> + 0x8609 (0x7fd337a6d609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default3]:frame #4: clone + 0x43 (0x7fd337838353 in /lib/x86_64-linux-gnu/libc.so.6)
[default3]:
W0702 16:11:04.525000 139691473110848 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2303216 closing signal SIGTERM
W0702 16:11:04.529000 139691473110848 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2303220 closing signal SIGTERM
W0702 16:11:04.534000 139691473110848 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2303221 closing signal SIGTERM
W0702 16:11:04.537000 139691473110848 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2303222 closing signal SIGTERM
W0702 16:11:04.540000 139691473110848 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2303223 closing signal SIGTERM
E0702 16:11:10.890000 139691473110848 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: -6) local_rank: 1 (pid: 2303217) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
============================================================
/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
------------------------------------------------------------
Failures:
[1]:
  time      : 2024-07-02_16:11:04
  host      : ip-26-0-169-132.ec2.internal
  rank      : 2 (local_rank: 2)
  exitcode  : -6 (pid: 2303218)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 2303218
[2]:
  time      : 2024-07-02_16:11:04
  host      : ip-26-0-169-132.ec2.internal
  rank      : 3 (local_rank: 3)
  exitcode  : -6 (pid: 2303219)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 2303219
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-07-02_16:11:04
  host      : ip-26-0-169-132.ec2.internal
  rank      : 1 (local_rank: 1)
  exitcode  : -6 (pid: 2303217)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 2303217
============================================================
srun: error: ip-26-0-169-132: task 0: Exited with exit code 1
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