132node/log.txt

/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
[2024-04-03 22:02:56,583] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
[2024-04-03 22:02:57,638] [WARNING] [runner.py:206:fetch_hostfile] Unable to find hostfile, will proceed with training with local resources only.
[2024-04-03 22:02:57,702] [INFO] [runner.py:585:main] cmd = /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyJsb2NhbGhvc3QiOiBbMCwgMSwgMiwgMywgNCwgNSwgNiwgN119 --master_addr=127.0.0.1 --master_port=29500 --no_python --no_local_rank --enable_each_rank_log=None /usr/bin/bash -c      cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 2     --pipeline-model-parallel-size 2     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 40     --hidden-size 5120     --ffn-hidden-size 13824     --num-attention-heads 40     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 100     --data-path /data/arxiv/tokenized_text_document     --vocab-file /data/arxiv/gpt2-vocab.json     --merge-file /data/arxiv/gpt2-merges.txt     --optimizer adamw     --adam-beta1 0.9     --adam-beta2 0.95     --adam-eps 1e-6     --lr 3e-4     --lr-decay-style cosine     --lr-warmup-iters 2000     --clip-grad 1.0     --weight-decay 0.1     --attention-dropout 0.1     --hidden-dropout 0.1     --tensorboard-dir /data/output/132node/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/132node/checkpoints     --deepspeed_config=/data/output/132node/ds_config.json      --zero-stage=0     --exit-interval 0     --no-masked-softmax-fusion     --no-bias-gelu-fusion     --no-bias-dropout-fusion     --use-torch-compile false     --use-fused-sdpa true     --use-fused-sdpa-with-recompute false          --bf16 --use_hpu --distributed-backend=hccl --hpu-deterministic --sequence-parallel --save /data/output/132node/checkpoints --save-interval 2000 --verify-checkpoint --verify-checkpoint-model-type LLAMA
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
[2024-04-03 22:02:59,064] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
[2024-04-03 22:03:00,115] [INFO] [launch.py:146:main] WORLD INFO DICT: {'localhost': [0, 1, 2, 3, 4, 5, 6, 7]}
[2024-04-03 22:03:00,115] [INFO] [launch.py:152:main] nnodes=1, num_local_procs=8, node_rank=0
[2024-04-03 22:03:00,115] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'localhost': [0, 1, 2, 3, 4, 5, 6, 7]})
[2024-04-03 22:03:00,115] [INFO] [launch.py:164:main] dist_world_size=8
[2024-04-03 22:03:00,115] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
[2024-04-03 22:03:01,731] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
[2024-04-03 22:03:01,736] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
[2024-04-03 22:03:01,736] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
[2024-04-03 22:03:01,738] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
[2024-04-03 22:03:01,740] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
[2024-04-03 22:03:01,749] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
[2024-04-03 22:03:01,830] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
[2024-04-03 22:03:01,845] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
--------------------------------------------------
DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at
      runtime if needed. Op compatibility means that your system
      meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
cpu_adam ............... [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
deepspeed_not_implemented  [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
--------------------------------------------------
DeepSpeed general environment info:
torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
torch version .................... 2.1.1a0+gitb51c9f6
deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
deepspeed wheel compiled w. ...... torch 2.1 
shared memory (/dev/shm) size .... 503.72 GB
fatal: detected dubious ownership in repository at '/Model-References'
To add an exception for this directory, call:

	git config --global --add safe.directory /Model-References
**** Git info for Megatron: git_hash=unknown git_branch=unknown ****
--------------------------------------------------
DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at
      runtime if needed. Op compatibility means that your system
      meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
cpu_adam ............... [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
deepspeed_not_implemented  [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
--------------------------------------------------
DeepSpeed general environment info:
torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
torch version .................... 2.1.1a0+gitb51c9f6
deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
deepspeed wheel compiled w. ...... torch 2.1 
shared memory (/dev/shm) size .... 503.72 GB
fatal: detected dubious ownership in repository at '/Model-References'
To add an exception for this directory, call:

	git config --global --add safe.directory /Model-References
**** Git info for Megatron: git_hash=unknown git_branch=unknown ****
--------------------------------------------------
DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at
      runtime if needed. Op compatibility means that your system
      meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
cpu_adam ............... [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
deepspeed_not_implemented  [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
--------------------------------------------------
DeepSpeed general environment info:
torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
torch version .................... 2.1.1a0+gitb51c9f6
deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
deepspeed wheel compiled w. ...... torch 2.1 
shared memory (/dev/shm) size .... 503.72 GB
--------------------------------------------------
DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at
      runtime if needed. Op compatibility means that your system
      meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
cpu_adam ............... [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
deepspeed_not_implemented  [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
--------------------------------------------------
DeepSpeed general environment info:
torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
torch version .................... 2.1.1a0+gitb51c9f6
deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
deepspeed wheel compiled w. ...... torch 2.1 
shared memory (/dev/shm) size .... 503.72 GB
--------------------------------------------------
DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at
      runtime if needed. Op compatibility means that your system
      meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
cpu_adam ............... [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
deepspeed_not_implemented  [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
--------------------------------------------------
DeepSpeed general environment info:
torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
torch version .................... 2.1.1a0+gitb51c9f6
deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
deepspeed wheel compiled w. ...... torch 2.1 
shared memory (/dev/shm) size .... 503.72 GB
fatal: detected dubious ownership in repository at '/Model-References'
To add an exception for this directory, call:

	git config --global --add safe.directory /Model-References
**** Git info for Megatron: git_hash=unknown git_branch=unknown ****
fatal: detected dubious ownership in repository at '/Model-References'
To add an exception for this directory, call:

	git config --global --add safe.directory /Model-References
**** Git info for Megatron: git_hash=unknown git_branch=unknown ****
fatal: detected dubious ownership in repository at '/Model-References'
To add an exception for this directory, call:

	git config --global --add safe.directory /Model-References
**** Git info for Megatron: git_hash=unknown git_branch=unknown ****
--------------------------------------------------
DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at
      runtime if needed. Op compatibility means that your system
      meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
cpu_adam ............... [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
deepspeed_not_implemented  [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
--------------------------------------------------
DeepSpeed general environment info:
torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
torch version .................... 2.1.1a0+gitb51c9f6
deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
deepspeed wheel compiled w. ...... torch 2.1 
shared memory (/dev/shm) size .... 503.72 GB
--------------------------------------------------
DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at
      runtime if needed. Op compatibility means that your system
      meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
cpu_adam ............... [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
deepspeed_not_implemented  [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
--------------------------------------------------
DeepSpeed general environment info:
torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
torch version .................... 2.1.1a0+gitb51c9f6
deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
deepspeed wheel compiled w. ...... torch 2.1 
shared memory (/dev/shm) size .... 503.72 GB
fatal: detected dubious ownership in repository at '/Model-References'
To add an exception for this directory, call:

	git config --global --add safe.directory /Model-References
**** Git info for Megatron: git_hash=unknown git_branch=unknown ****
using world size: 8, data-parallel-size: 2, tensor-model-parallel size: 2, pipeline-model-parallel size: 2 
accumulate and all-reduce gradients in fp32 for bfloat16 data type.
using torch.bfloat16 for parameters ...
------------------------ arguments ------------------------
  accumulate_allreduce_grads_in_fp32 .............. True
  activation_func_type ............................ swiglu
  adam_beta1 ...................................... 0.9
  adam_beta2 ...................................... 0.95
  adam_eps ........................................ 1e-06
  adlr_autoresume ................................. False
  adlr_autoresume_interval ........................ 1000
  aml_data_download_path .......................... None
  apply_layernorm_weight_plus_one ................. False
  apply_query_key_layer_scaling ................... True
  apply_residual_connection_post_layernorm ........ False
  attention_dropout ............................... 0.1
  attention_softmax_in_fp32 ....................... False
  bert_binary_head ................................ True
  bert_load ....................................... None
  bf16 ............................................ True
  bias_dropout_fusion ............................. False
  bias_gelu_fusion ................................ False
  biencoder_projection_dim ........................ 0
  biencoder_shared_query_context_model ............ False
  block_data_path ................................. None
  cache_fp8_weight ................................ False
  cache_fp8_weight_fwd ............................ True
  checkpoint_activations .......................... False
  checkpoint_activations_granularity .............. full
  checkpoint_in_cpu ............................... False
  checkpoint_num_layers ........................... 1
  clearml_config_path ............................. None
  clearml_continue_exp ............................ False
  clearml_exp_name ................................ None
  clip_grad ....................................... 1.0
  compression_training ............................ False
  consumed_train_samples .......................... 0
  consumed_train_tokens ........................... 0
  consumed_valid_samples .......................... 0
  contigious_checkpointing ........................ False
  cpu_optimizer ................................... False
  cpu_torch_adam .................................. False
  create_moe_param_group .......................... False
  curriculum_learning ............................. False
  data_idx_path ................................... None
  data_impl ....................................... infer
  data_parallel_size .............................. 2
  data_path ....................................... ['/data/arxiv/tokenized_text_document']
  data_sharding ................................... True
  dataloader_type ................................. single
  DDP_impl ........................................ local
  decoder_seq_length .............................. None
  deepscale ....................................... False
  deepscale_config ................................ None
  deepspeed ....................................... True
  deepspeed_activation_checkpointing .............. False
  deepspeed_config ................................ /data/output/132node/ds_config.json
  deepspeed_mpi ................................... False
  distribute_checkpointed_activations ............. False
  distributed_backend ............................. hccl
  do_layernorm_bias_weight_decay .................. False
  do_pretrain_validation .......................... False
  ds_inference .................................... False
  ds_pipeline_enabled ............................. True
  embed_layernorm ................................. False
  embedding_path .................................. None
  enable_expert_tensor_parallelism ................ False
  encoder_seq_length .............................. 2048
  eod_mask_loss ................................... False
  eval_interval ................................... 100
  eval_iters ...................................... 10
  eval_loss_exit_value ............................ None
  eval_micro_batch_size ........................... 1
  evidence_data_path .............................. None
  exit_duration_in_mins ........................... None
  exit_interval ................................... 0
  expert_interval ................................. 2
  ffn_hidden_coeff ................................ 2.6666666666666665
  ffn_hidden_size ................................. 13824
  finetune ........................................ False
  fix_position_emb_redundant_alloc ................ False
  flatten_linear_operands ......................... False
  fp16 ............................................ False
  fp16_lm_cross_entropy ........................... False
  fp32_residual_connection ........................ False
  global_batch_size ............................... 256
  hidden_dropout .................................. 0.1
  hidden_size ..................................... 5120
  hidden_size_teacher ............................. None
  hpu_deterministic ............................... True
  hpu_fp8_format .................................. e5m2
  hpu_fp8_measure_interval ........................ 10
  hysteresis ...................................... 2
  ict_head_size ................................... None
  ict_load ........................................ None
  img_dim ......................................... 224
  indexer_batch_size .............................. 128
  indexer_log_interval ............................ 1000
  inference ....................................... False
  init_method_std ................................. 0.02
  init_method_xavier_uniform ...................... False
  initial_loss_scale .............................. 4294967296
  kd .............................................. False
  kd_alpha_ce ..................................... 1
  kd_beta_ce ...................................... 1
  kd_temp ......................................... 1.0
  kill_switch_path ................................ None
  kv_channels ..................................... 128
  layernorm_epsilon ............................... 1e-06
  layernorm_type .................................. rmsnorm
  lazy_mpu_init ................................... None
  load ............................................ /data/output/132node/checkpoints
  load_teacher .................................... None
  local_rank ...................................... 0
  log_batch_size_to_tensorboard ................... True
  log_bwd_grads ................................... False
  log_fwd_activations ............................. False
  log_interval .................................... 10
  log_learning_rate_to_tensorboard ................ True
  log_loss_scale_to_tensorboard ................... True
  log_model_inputs ................................ False
  log_num_zeros_in_grad ........................... False
  log_optimizer_states_to_tensorboard ............. False
  log_params_norm ................................. False
  log_timers_to_tensorboard ....................... True
  log_validation_ppl_to_tensorboard ............... True
  loss_scale ...................................... None
  loss_scale_window ............................... 1000
  lr .............................................. 0.0003
  lr_decay_iters .................................. None
  lr_decay_samples ................................ None
  lr_decay_style .................................. cosine
  lr_decay_tokens ................................. None
  lr_warmup_fraction .............................. None
  lr_warmup_iters ................................. 2000
  lr_warmup_samples ............................... 0
  lr_warmup_tokens ................................ None
  make_vocab_size_divisible_by .................... 128
  mask_prob ....................................... 0.15
  mask_tensor_adding .............................. False
  masked_softmax_fusion ........................... False
  max_position_embeddings ......................... None
  memory_centric_tiled_linear ..................... False
  merge_file ...................................... /data/arxiv/gpt2-merges.txt
  micro_batch_size ................................ 1
  min_loss_scale .................................. 1.0
  min_lr .......................................... 0.0
  mlp_type ........................................ standard
  mmap_warmup ..................................... False
  moe_eval_capacity_factor ........................ 1.0
  moe_expert_parallel_size ........................ 1
  moe_loss_coeff .................................. 0.1
  moe_min_capacity ................................ 4
  moe_token_dropping .............................. True
  moe_train_capacity_factor ....................... 1.0
  mos ............................................. False
  no_bias ......................................... True
  no_cuda ......................................... False
  no_load_lr_state ................................ False
  no_load_optim ................................... None
  no_load_rng ..................................... None
  no_pipeline_parallel ............................ False
  no_save_optim ................................... None
  no_save_rng ..................................... None
  no_scaled_init .................................. False
  num_attention_heads ............................. 40
  num_attention_heads_teacher ..................... None
  num_channels .................................... 3
  num_classes ..................................... 1000
  num_experts ..................................... [1]
  num_experts_teacher ............................. [1]
  num_key_value_heads ............................. 40
  num_layers ...................................... 40
  num_layers_per_virtual_pipeline_stage ........... None
  num_layers_teacher .............................. None
  num_workers ..................................... 2
  onnx_safe ....................................... None
  openai_gelu ..................................... False
  optimizer ....................................... adamw
  override_lr_scheduler ........................... False
  params_dtype .................................... torch.bfloat16
  partition_activations ........................... False
  patch_dim ....................................... 16
  pipeline_model_parallel_size .................... 2
  position_embedding_type ......................... PositionEmbeddingType.rotary
  profile ......................................... None
  profile_backward ................................ False
  profile_steps ................................... 2,3
  query_in_block_prob ............................. 0.1
  rampup_batch_size ............................... None
  rank ............................................ 0
  remote_device ................................... none
  reset_attention_mask ............................ False
  reset_iteration ................................. False
  reset_position_ids .............................. False
  retriever_report_topk_accuracies ................ []
  retriever_score_scaling ......................... False
  retriever_seq_length ............................ 256
  sample_rate ..................................... 1.0
  save ............................................ /data/output/132node/checkpoints
  save_interval ................................... 2000
  scatter_gather_tensors_in_pipeline .............. True
  scattered_embeddings ............................ False
  seed ............................................ 1234
  seq_length ...................................... 2048
  sequence_parallel ............................... True
  sgd_momentum .................................... 0.9
  short_seq_prob .................................. 0.1
  skip_train ...................................... False
  split ........................................... 969, 30, 1
  split_transformers .............................. False
  synchronize_each_layer .......................... False
  tensor_logger_max_iter .......................... 0
  tensor_logger_path .............................. None
  tensor_model_parallel_size ...................... 2
  tensorboard_dir ................................. /data/output/132node/tensorboard
  tensorboard_log_interval ........................ 1
  tensorboard_queue_size .......................... 1000
  test_data_path .................................. None
  tile_factor ..................................... 1
  titles_data_path ................................ None
  tokenizer_eod_id ................................ None
  tokenizer_model_file ............................ None
  tokenizer_type .................................. GPT2BPETokenizer
  topk ............................................ 1
  train_data_path ................................. None
  train_iters ..................................... 10000
  train_samples ................................... None
  train_tokens .................................... None
  universal_checkpoint ............................ False
  use_checkpoint_lr_scheduler ..................... False
  use_contiguous_buffers_in_ddp ................... True
  use_cpu_initialization .......................... None
  use_fused_sdpa .................................. True
  use_fused_sdpa_with_recompute ................... False
  use_hpu ......................................... True
  use_hpu_fp8_transformer_engine .................. False
  use_hpu_graphs .................................. False
  use_one_sent_docs ............................... False
  use_pin_memory .................................. False
  use_rotary_v2 ................................... False
  use_seq_len_plus_one_tokens ..................... True
  use_torch_compile ............................... False
  use_tutel ....................................... False
  valid_data_path ................................. None
  verify_checkpoint ............................... True
  verify_checkpoint_model_type .................... LLAMA
  verify_tp_workers ............................... False
  verify_tp_workers_hash .......................... False
  virtual_pipeline_model_parallel_size ............ None
  vocab_extra_ids ................................. 0
  vocab_file ...................................... /data/arxiv/gpt2-vocab.json
  weight_decay .................................... 0.1
  world_size ...................................... 8
  zero_allgather_bucket_size ...................... 0.0
  zero_contigious_gradients ....................... False
  zero_reduce_bucket_size ......................... 0.0
  zero_reduce_scatter ............................. False
  zero_stage ...................................... 0
-------------------- end of arguments ---------------------
setting number of micro-batches to constant 128
setting number of micro-batches to constant 128
> building GPT2BPETokenizer tokenizer ...
fatal: detected dubious ownership in repository at '/Model-References'
To add an exception for this directory, call:

	git config --global --add safe.directory /Model-References
**** Git info for Megatron: git_hash=unknown git_branch=unknown ****
_initialize_distributed: Initializing with below params:
args.local_rank: 6
args.world_size: 8
args.rank: 6
args.distributed_backend: hccl
_initialize_distributed: Initializing with below params:
args.local_rank: 1
args.world_size: 8
args.rank: 1
args.distributed_backend: hccl
_initialize_distributed: Initializing with below params:
args.local_rank: 3
args.world_size: 8
args.rank: 3
args.distributed_backend: hccl
_initialize_distributed: Initializing with below params:
args.local_rank: 2
args.world_size: 8
args.rank: 2
args.distributed_backend: hccl
--------------------------------------------------
DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at
      runtime if needed. Op compatibility means that your system
      meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
cpu_adam ............... [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]
deepspeed_not_implemented  [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
--------------------------------------------------
DeepSpeed general environment info:
torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
torch version .................... 2.1.1a0+gitb51c9f6
deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
deepspeed wheel compiled w. ...... torch 2.1 
shared memory (/dev/shm) size .... 503.72 GB
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
hccl device_count:  8
[2024-04-03 22:03:03,241] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
[2024-04-03 22:03:03,241] [INFO] [comm.py:637:init_distributed] cdb=None
fatal: detected dubious ownership in repository at '/Model-References'
To add an exception for this directory, call:

	git config --global --add safe.directory /Model-References
**** Git info for Megatron: git_hash=unknown git_branch=unknown ****
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
hccl device_count:  8
[2024-04-03 22:03:03,252] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
[2024-04-03 22:03:03,252] [INFO] [comm.py:637:init_distributed] cdb=None
_initialize_distributed: Initializing with below params:
args.local_rank: 4
args.world_size: 8
args.rank: 4
args.distributed_backend: hccl
 > padded vocab (size: 50257) with 175 dummy tokens (new size: 50432)
_initialize_distributed: Initializing with below params:
args.local_rank: 0
args.world_size: 8
args.rank: 0
args.distributed_backend: hccl
> setting tensorboard ...
_initialize_distributed: Initializing with below params:
args.local_rank: 7
args.world_size: 8
args.rank: 7
args.distributed_backend: hccl
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
hccl device_count:  8
[2024-04-03 22:03:03,289] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
[2024-04-03 22:03:03,289] [INFO] [comm.py:637:init_distributed] cdb=None
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
hccl device_count:  8
[2024-04-03 22:03:03,296] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
[2024-04-03 22:03:03,296] [INFO] [comm.py:637:init_distributed] cdb=None
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
hccl device_count:  8
[2024-04-03 22:03:03,326] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
[2024-04-03 22:03:03,327] [INFO] [comm.py:637:init_distributed] cdb=None
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
hccl device_count:  8
> initializing torch distributed ...
[2024-04-03 22:03:03,343] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
[2024-04-03 22:03:03,343] [INFO] [comm.py:637:init_distributed] cdb=None
[2024-04-03 22:03:03,343] [INFO] [comm.py:668:init_distributed] Initializing TorchBackend in DeepSpeed with backend hccl
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
hccl device_count:  8
[2024-04-03 22:03:03,345] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
[2024-04-03 22:03:03,345] [INFO] [comm.py:637:init_distributed] cdb=None
_initialize_distributed: Initializing with below params:
args.local_rank: 5
args.world_size: 8
args.rank: 5
args.distributed_backend: hccl
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/hpu/__init__.py:158: UserWarning: torch.hpu.setDeterministic is deprecated and will be removed in next release. Please use torch.use_deterministic_algorithms instead.
  warnings.warn(
hccl device_count:  8
[2024-04-03 22:03:03,441] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
[2024-04-03 22:03:03,441] [INFO] [comm.py:637:init_distributed] cdb=None
> initializing tensor model parallel with size 2
> initializing pipeline model parallel with size 2
> setting random seeds to 1234 ...
> initializing model parallel cuda seeds on global rank 0, model parallel rank 0, and data parallel rank 0 with model parallel seed: 3952 and data parallel seed: 1234
============================= HABANA PT BRIDGE CONFIGURATION =========================== 
 PT_HPU_LAZY_MODE = 1
 PT_RECIPE_CACHE_PATH = 
 PT_CACHE_FOLDER_DELETE = 0
 PT_HPU_RECIPE_CACHE_CONFIG = 
 PT_HPU_MAX_COMPOUND_OP_SIZE = 9223372036854775807
 PT_HPU_LAZY_ACC_PAR_MODE = 0
 PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES = 0
---------------------------: System Configuration :---------------------------
Num CPU Cores : 160
CPU RAM       : 1056375244 KB
------------------------------------------------------------------------------
> compiling dataset index builder ...
make: Entering directory '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/data'
make: Nothing to be done for 'default'.
make: Leaving directory '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/data'
>>> done with dataset index builder. Compilation time: 0.072 seconds
WARNING: constraints for invoking optimized fused softmax kernel are not met. We default back to unfused kernel invocations.
> compiling and loading fused kernels ...
>>> done with compiling and loading fused kernels. Compilation time: 0.005 seconds
time to initialize megatron (seconds): 29.272
[after megatron is initialized] datetime: 2024-04-03 22:03:09 
building LLaMA model ...
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
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*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
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*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ********************************* Using FusedSDPA ******************

*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
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*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ********************************* Using FusedSDPA ******************

*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/weight_sharing.py:53: UserWarning: "hpu:X" notation is not supported by Gaudi PyTorch intergration bridge. Please change to "hpu" without index (Triggered internally at /npu-stack/pytorch-integration/pytorch_helpers/lazy_to_backend.cpp:53.)
  return super().__torch_function__(func, types, new_args, kwargs)
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/weight_sharing.py:53: UserWarning: "hpu:X" notation is not supported by Gaudi PyTorch intergration bridge. Please change to "hpu" without index (Triggered internally at /npu-stack/pytorch-integration/pytorch_helpers/lazy_to_backend.cpp:53.)
  return super().__torch_function__(func, types, new_args, kwargs)
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/weight_sharing.py:53: UserWarning: "hpu:X" notation is not supported by Gaudi PyTorch intergration bridge. Please change to "hpu" without index (Triggered internally at /npu-stack/pytorch-integration/pytorch_helpers/lazy_to_backend.cpp:53.)
  return super().__torch_function__(func, types, new_args, kwargs)
*************** Using FusedSDPA ******************
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/weight_sharing.py:53: UserWarning: "hpu:X" notation is not supported by Gaudi PyTorch intergration bridge. Please change to "hpu" without index (Triggered internally at /npu-stack/pytorch-integration/pytorch_helpers/lazy_to_backend.cpp:53.)
  return super().__torch_function__(func, types, new_args, kwargs)
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/weight_sharing.py:53: UserWarning: "hpu:X" notation is not supported by Gaudi PyTorch intergration bridge. Please change to "hpu" without index (Triggered internally at /npu-stack/pytorch-integration/pytorch_helpers/lazy_to_backend.cpp:53.)
  return super().__torch_function__(func, types, new_args, kwargs)
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
 > number of parameters on (tensor, pipeline) model parallel rank (1, 0): 3301253120
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/weight_sharing.py:53: UserWarning: "hpu:X" notation is not supported by Gaudi PyTorch intergration bridge. Please change to "hpu" without index (Triggered internally at /npu-stack/pytorch-integration/pytorch_helpers/lazy_to_backend.cpp:53.)
  return super().__torch_function__(func, types, new_args, kwargs)
/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/weight_sharing.py:53: UserWarning: "hpu:X" notation is not supported by Gaudi PyTorch intergration bridge. Please change to "hpu" without index (Triggered internally at /npu-stack/pytorch-integration/pytorch_helpers/lazy_to_backend.cpp:53.)
  return super().__torch_function__(func, types, new_args, kwargs)
 > number of parameters on (tensor, pipeline) model parallel rank (0, 1): 3301258240
[2024-04-03 22:03:09,344] [INFO] [utils.py:824:see_memory_usage] Before Building Model
 > number of parameters on (tensor, pipeline) model parallel rank (1, 1): 3301258240
[2024-04-03 22:03:09,347] [INFO] [utils.py:825:see_memory_usage] MA 0.01 GB         Max_MA 0.01 GB         CA 0.0 GB         Max_CA 0 GB 
[2024-04-03 22:03:09,348] [INFO] [utils.py:832:see_memory_usage] CPU Virtual Memory:  used = 345.07 GB, percent = 34.3%
SEED_LAYERS=False BASE_SEED=1234 SEED_FN=None
Using topology: {ProcessCoord(pipe=0, data=0, model=0): 0, ProcessCoord(pipe=0, data=0, model=1): 1, ProcessCoord(pipe=0, data=1, model=0): 2, ProcessCoord(pipe=0, data=1, model=1): 3, ProcessCoord(pipe=1, data=0, model=0): 4, ProcessCoord(pipe=1, data=0, model=1): 5, ProcessCoord(pipe=1, data=1, model=0): 6, ProcessCoord(pipe=1, data=1, model=1): 7}
[2024-04-03 22:03:09,350] [INFO] [module.py:375:_partition_layers] Partitioning pipeline stages with method type:transformer
stage=0 layers=23
     0: _to_float16
     1: EmbeddingPipe
     2: <lambda>
     3: ParallelTransformerLayerPipe
     4: ParallelTransformerLayerPipe
     5: ParallelTransformerLayerPipe
     6: ParallelTransformerLayerPipe
     7: ParallelTransformerLayerPipe
     8: ParallelTransformerLayerPipe
     9: ParallelTransformerLayerPipe
    10: ParallelTransformerLayerPipe
    11: ParallelTransformerLayerPipe
    12: ParallelTransformerLayerPipe
    13: ParallelTransformerLayerPipe
    14: ParallelTransformerLayerPipe
    15: ParallelTransformerLayerPipe
    16: ParallelTransformerLayerPipe
    17: ParallelTransformerLayerPipe
    18: ParallelTransformerLayerPipe
    19: ParallelTransformerLayerPipe
    20: ParallelTransformerLayerPipe
    21: ParallelTransformerLayerPipe
    22: ParallelTransformerLayerPipe
stage=1 layers=25
    23: ParallelTransformerLayerPipe
    24: ParallelTransformerLayerPipe
    25: ParallelTransformerLayerPipe
    26: ParallelTransformerLayerPipe
    27: ParallelTransformerLayerPipe
    28: ParallelTransformerLayerPipe
    29: ParallelTransformerLayerPipe
    30: ParallelTransformerLayerPipe
    31: ParallelTransformerLayerPipe
    32: ParallelTransformerLayerPipe
    33: ParallelTransformerLayerPipe
    34: ParallelTransformerLayerPipe
    35: ParallelTransformerLayerPipe
    36: ParallelTransformerLayerPipe
    37: ParallelTransformerLayerPipe
    38: ParallelTransformerLayerPipe
    39: ParallelTransformerLayerPipe
    40: ParallelTransformerLayerPipe
    41: ParallelTransformerLayerPipe
    42: ParallelTransformerLayerPipe
    43: <lambda>
    44: WrapName
    45: WrapName
    46: <lambda>
    47: float16_to_fp32
  loss: CrossEntropy
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
*************** Using FusedSDPA ******************
[2024-04-03 22:03:09,470] [INFO] [utils.py:824:see_memory_usage] After Building Model
[2024-04-03 22:03:09,474] [INFO] [utils.py:825:see_memory_usage] MA 0.01 GB         Max_MA 0.01 GB         CA 0.0 GB         Max_CA 0 GB 
[2024-04-03 22:03:09,474] [INFO] [utils.py:832:see_memory_usage] CPU Virtual Memory:  used = 345.56 GB, percent = 34.3%
 > number of parameters on (tensor, pipeline) model parallel rank (0, 0): 3301253120
> learning rate decay style: cosine
DeepSpeed is enabled.
[2024-04-03 22:03:09,479] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed info: version=0.12.4+hpu.synapse.v1.14.0, git-hash=fad45b2, git-branch=1.14.0
[2024-04-03 22:03:10,368] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Flops Profiler Enabled: False
[2024-04-03 22:03:10,369] [INFO] [logging.py:96:log_dist] [Rank 0] Using client Optimizer as basic optimizer
[2024-04-03 22:03:10,369] [INFO] [logging.py:96:log_dist] [Rank 0] Removing param_group that has no 'params' in the basic Optimizer
[2024-04-03 22:03:10,371] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Basic Optimizer = AdamW
[2024-04-03 22:03:10,371] [INFO] [logging.py:96:log_dist] [Rank 0] Creating BF16 optimizer
[2024-04-03 22:03:10,445] [INFO] [utils.py:824:see_memory_usage] begin bf16_optimizer
[2024-04-03 22:03:10,448] [INFO] [utils.py:825:see_memory_usage] MA 6.16 GB         Max_MA 6.18 GB         CA 0.0 GB         Max_CA 0 GB 
[2024-04-03 22:03:10,448] [INFO] [utils.py:832:see_memory_usage] CPU Virtual Memory:  used = 348.0 GB, percent = 34.5%
[2024-04-03 22:03:10,513] [INFO] [utils.py:824:see_memory_usage] before initializing group 0
[2024-04-03 22:03:10,516] [INFO] [utils.py:825:see_memory_usage] MA 6.16 GB         Max_MA 0.0 GB         CA 0.0 GB         Max_CA 0 GB 
[2024-04-03 22:03:10,516] [INFO] [utils.py:832:see_memory_usage] CPU Virtual Memory:  used = 348.08 GB, percent = 34.6%
[2024-04-03 22:03:10,777] [INFO] [engine.py:139:__init__] is_pipe_partitioned= False is_grad_partitioned= False
[2024-04-03 22:03:10,789] [INFO] [engine.py:139:__init__] is_pipe_partitioned= False is_grad_partitioned= False
[2024-04-03 22:03:10,837] [INFO] [engine.py:139:__init__] is_pipe_partitioned= False is_grad_partitioned= False
[2024-04-03 22:03:10,838] [INFO] [engine.py:139:__init__] is_pipe_partitioned= False is_grad_partitioned= False
[2024-04-03 22:03:10,861] [INFO] [engine.py:139:__init__] is_pipe_partitioned= False is_grad_partitioned= False
[2024-04-03 22:03:11,089] [INFO] [utils.py:824:see_memory_usage] after initializing group 0
[2024-04-03 22:03:11,092] [INFO] [utils.py:825:see_memory_usage] MA 6.16 GB         Max_MA 12.31 GB         CA 0.0 GB         Max_CA 0 GB 
[2024-04-03 22:03:11,092] [INFO] [utils.py:832:see_memory_usage] CPU Virtual Memory:  used = 348.52 GB, percent = 34.6%
[2024-04-03 22:03:11,147] [INFO] [utils.py:824:see_memory_usage] before initializing group 1
[2024-04-03 22:03:11,150] [INFO] [utils.py:825:see_memory_usage] MA 6.16 GB         Max_MA 0.0 GB         CA 0.0 GB         Max_CA 0 GB 
[2024-04-03 22:03:11,150] [INFO] [utils.py:832:see_memory_usage] CPU Virtual Memory:  used = 348.52 GB, percent = 34.6%
[2024-04-03 22:03:11,231] [INFO] [engine.py:139:__init__] is_pipe_partitioned= False is_grad_partitioned= False
[2024-04-03 22:03:11,236] [INFO] [utils.py:824:see_memory_usage] after initializing group 1
[2024-04-03 22:03:11,239] [INFO] [utils.py:825:see_memory_usage] MA 24.61 GB         Max_MA 24.61 GB         CA 0.0 GB         Max_CA 0 GB 
[2024-04-03 22:03:11,239] [INFO] [utils.py:832:see_memory_usage] CPU Virtual Memory:  used = 348.52 GB, percent = 34.6%
[2024-04-03 22:03:11,240] [INFO] [engine.py:139:__init__] is_pipe_partitioned= False is_grad_partitioned= False
[2024-04-03 22:03:11,294] [INFO] [utils.py:824:see_memory_usage] before initialize_optimizer
[2024-04-03 22:03:11,297] [INFO] [utils.py:825:see_memory_usage] MA 24.61 GB         Max_MA 0.0 GB         CA 0.0 GB         Max_CA 0 GB 
[2024-04-03 22:03:11,297] [INFO] [utils.py:832:see_memory_usage] CPU Virtual Memory:  used = 348.55 GB, percent = 34.6%
[2024-04-03 22:03:11,348] [INFO] [utils.py:824:see_memory_usage] end initialize_optimizer
[2024-04-03 22:03:11,352] [INFO] [utils.py:825:see_memory_usage] MA 24.61 GB         Max_MA 0.0 GB         CA 0.0 GB         Max_CA 0 GB 
[2024-04-03 22:03:11,352] [INFO] [utils.py:832:see_memory_usage] CPU Virtual Memory:  used = 348.52 GB, percent = 34.6%
[2024-04-03 22:03:11,403] [INFO] [utils.py:824:see_memory_usage] end bf16_optimizer
[2024-04-03 22:03:11,406] [INFO] [utils.py:825:see_memory_usage] MA 24.61 GB         Max_MA 0.0 GB         CA 0.0 GB         Max_CA 0 GB 
[2024-04-03 22:03:11,406] [INFO] [utils.py:832:see_memory_usage] CPU Virtual Memory:  used = 348.52 GB, percent = 34.6%
[2024-04-03 22:03:11,407] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Final Optimizer = BF16_Optimizer
[2024-04-03 22:03:11,407] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed using client LR scheduler
[2024-04-03 22:03:11,407] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed LR Scheduler = <megatron.learning_rates.AnnealingLR object at 0x7fe01c1a9db0>
[2024-04-03 22:03:11,407] [INFO] [logging.py:96:log_dist] [Rank 0] step=0, skipped=0, lr=[0.0, 0.0], mom=[(0.9, 0.95), (0.9, 0.95)]
[2024-04-03 22:03:11,408] [INFO] [config.py:992:print] DeepSpeedEngine configuration:
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   activation_checkpointing_config  {
    "partition_activations": false, 
    "contiguous_memory_optimization": false, 
    "cpu_checkpointing": false, 
    "number_checkpoints": null, 
    "synchronize_checkpoint_boundary": false, 
    "profile": false
}
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True}
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   amp_enabled .................. False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   amp_params ................... False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   autotuning_config ............ {
    "enabled": false, 
    "start_step": null, 
    "end_step": null, 
    "metric_path": null, 
    "arg_mappings": null, 
    "metric": "throughput", 
    "model_info": null, 
    "results_dir": "autotuning_results", 
    "exps_dir": "autotuning_exps", 
    "overwrite": true, 
    "fast": true, 
    "start_profile_step": 3, 
    "end_profile_step": 5, 
    "tuner_type": "gridsearch", 
    "tuner_early_stopping": 5, 
    "tuner_num_trials": 50, 
    "model_info_path": null, 
    "mp_size": 1, 
    "max_train_batch_size": null, 
    "min_train_batch_size": 1, 
    "max_train_micro_batch_size_per_gpu": 1.024000e+03, 
    "min_train_micro_batch_size_per_gpu": 1, 
    "num_tuning_micro_batch_sizes": 3
}
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   bfloat16_accumulate_grads_via_hooks  True
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   bfloat16_enabled ............. True
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   checkpoint_parallel_write_pipeline  False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   checkpoint_tag_validation_enabled  True
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   checkpoint_tag_validation_fail  False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   comms_config ................. <deepspeed.comm.config.DeepSpeedCommsConfig object at 0x7fe01c1a9810>
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   communication_data_type ...... None
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   compression_config ........... {'weight_quantization': {'shared_parameters': {'enabled': False, 'quantizer_kernel': False, 'schedule_offset': 0, 'quantize_groups': 1, 'quantize_verbose': False, 'quantization_type': 'symmetric', 'quantize_weight_in_forward': False, 'rounding': 'nearest', 'fp16_mixed_quantize': False, 'quantize_change_ratio': 0.001}, 'different_groups': {}}, 'activation_quantization': {'shared_parameters': {'enabled': False, 'quantization_type': 'symmetric', 'range_calibration': 'dynamic', 'schedule_offset': 1000}, 'different_groups': {}}, 'sparse_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'row_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'head_pruning': {'shared_parameters': {'enabled': False, 'method': 'topk', 'schedule_offset': 1000}, 'different_groups': {}}, 'channel_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'layer_reduction': {'enabled': False}}
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   curriculum_enabled_legacy .... False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   curriculum_params_legacy ..... False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   data_efficiency_config ....... {'enabled': False, 'seed': 1234, 'data_sampling': {'enabled': False, 'num_epochs': 1000, 'num_workers': 0, 'curriculum_learning': {'enabled': False}}, 'data_routing': {'enabled': False, 'random_ltd': {'enabled': False, 'layer_token_lr_schedule': {'enabled': False}}}}
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   data_efficiency_enabled ...... False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   dataloader_drop_last ......... False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   disable_allgather ............ False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   dump_state ................... False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   dynamic_loss_scale_args ...... None
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   eigenvalue_enabled ........... False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   eigenvalue_gas_boundary_resolution  1
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   eigenvalue_layer_name ........ bert.encoder.layer
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   eigenvalue_layer_num ......... 0
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   eigenvalue_max_iter .......... 100
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   eigenvalue_stability ......... 1e-06
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   eigenvalue_tol ............... 0.01
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   eigenvalue_verbose ........... False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   elasticity_enabled ........... False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   flops_profiler_config ........ {
    "enabled": false, 
    "recompute_fwd_factor": 0.0, 
    "profile_step": 1, 
    "module_depth": -1, 
    "top_modules": 1, 
    "detailed": true, 
    "output_file": null
}
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   fp16_auto_cast ............... None
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   fp16_enabled ................. False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   fp16_master_weights_and_gradients  False
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   global_rank .................. 0
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   grad_accum_dtype ............. None
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   gradient_accumulation_steps .. 128
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   gradient_clipping ............ 1.0
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   gradient_predivide_factor .... 1.0
[2024-04-03 22:03:11,408] [INFO] [config.py:996:print]   hybrid_engine ................ enabled=False max_out_tokens=512 inference_tp_size=1 release_inference_cache=False pin_parameters=True tp_gather_partition_size=8
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   initial_dynamic_scale ........ 1
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   load_universal_checkpoint .... False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   loss_scale ................... 1.0
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   memory_breakdown ............. False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   mics_hierarchial_params_gather  False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   mics_shard_size .............. -1
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   monitor_config ............... tensorboard=TensorBoardConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') wandb=WandbConfig(enabled=False, group=None, team=None, project='deepspeed') csv_monitor=CSVConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') enabled=False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   nebula_config ................ {
    "enabled": false, 
    "persistent_storage_path": null, 
    "persistent_time_interval": 100, 
    "num_of_version_in_retention": 2, 
    "enable_nebula_load": true, 
    "load_path": null
}
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   optimizer_legacy_fusion ...... False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   optimizer_name ............... None
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   optimizer_params ............. None
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0, 'pipe_partitioned': False, 'grad_partitioned': False}
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   pld_enabled .................. False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   pld_params ................... False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   prescale_gradients ........... False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   scheduler_name ............... None
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   scheduler_params ............. None
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   seq_parallel_communication_data_type  torch.float32
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   sparse_attention ............. None
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   sparse_gradients_enabled ..... False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   steps_per_print .............. 10
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   train_batch_size ............. 256
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   train_micro_batch_size_per_gpu  1
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   use_data_before_expert_parallel_  False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   use_node_local_storage ....... False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   wall_clock_breakdown ......... False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   weight_quantization_config ... None
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   world_size ................... 2
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   zero_allow_comm_data_type_fp32  False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   zero_allow_untested_optimizer  False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   zero_config .................. stage=0 contiguous_gradients=True reduce_scatter=False reduce_bucket_size=500,000,000 use_multi_rank_bucket_allreduce=True allgather_partitions=True allgather_bucket_size=500,000,000 overlap_comm=False load_from_fp32_weights=True elastic_checkpoint=False offload_param=None offload_optimizer=None sub_group_size=1,000,000,000 cpu_offload_param=None cpu_offload_use_pin_memory=None cpu_offload=None prefetch_bucket_size=50,000,000 param_persistence_threshold=100,000 model_persistence_threshold=sys.maxsize max_live_parameters=1,000,000,000 max_reuse_distance=1,000,000,000 gather_16bit_weights_on_model_save=False stage3_gather_fp16_weights_on_model_save=False use_all_reduce_for_fetch_params=False ignore_unused_parameters=True legacy_stage1=False round_robin_gradients=False zero_hpz_partition_size=1 zero_quantized_weights=False zero_quantized_nontrainable_weights=False zero_quantized_gradients=False mics_shard_size=-1 mics_hierarchical_params_gather=False memory_efficient_linear=True pipeline_loading_checkpoint=False override_module_apply=True
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   zero_enabled ................. False
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   zero_force_ds_cpu_optimizer .. True
[2024-04-03 22:03:11,409] [INFO] [config.py:996:print]   zero_optimization_stage ...... 0
[2024-04-03 22:03:11,409] [INFO] [config.py:982:print_user_config]   json = {
    "train_batch_size": 256, 
    "train_micro_batch_size_per_gpu": 1, 
    "steps_per_print": 10, 
    "gradient_clipping": 1.0, 
    "zero_optimization": {
        "stage": 0
    }, 
    "bf16": {
        "enabled": true, 
        "accumulate_grads_via_hooks": true
    }, 
    "fp16": {
        "enabled": false
    }, 
    "wall_clock_breakdown": false, 
    "pipeline": {
        "pipe_partitioned": false, 
        "grad_partitioned": false
    }
}
[2024-04-03 22:03:11,409] [INFO] [engine.py:99:__init__] CONFIG: micro_batches=128 micro_batch_size=1
[2024-04-03 22:03:11,409] [INFO] [engine.py:139:__init__] is_pipe_partitioned= False is_grad_partitioned= False
[2024-04-03 22:03:12,129] [INFO] [engine.py:180:__init__] RANK=4 STAGE=1 LAYERS=25 [23, 48) STAGE_PARAMS=3301258240 (3301.258M) TOTAL_PARAMS=13205022720 (13205.023M) UNIQUE_PARAMS=13205022720 (13205.023M)
[2024-04-03 22:03:12,129] [INFO] [engine.py:180:__init__] RANK=1 STAGE=0 LAYERS=23 [0, 23) STAGE_PARAMS=3301253120 (3301.253M) TOTAL_PARAMS=13205022720 (13205.023M) UNIQUE_PARAMS=13205022720 (13205.023M)
[2024-04-03 22:03:12,129] [INFO] [engine.py:180:__init__] RANK=5 STAGE=1 LAYERS=25 [23, 48) STAGE_PARAMS=3301258240 (3301.258M) TOTAL_PARAMS=13205022720 (13205.023M) UNIQUE_PARAMS=13205022720 (13205.023M)
[2024-04-03 22:03:12,130] [INFO] [engine.py:180:__init__] RANK=0 STAGE=0 LAYERS=23 [0, 23) STAGE_PARAMS=3301253120 (3301.253M) TOTAL_PARAMS=13205022720 (13205.023M) UNIQUE_PARAMS=13205022720 (13205.023M)
[2024-04-03 22:03:12,132] [WARNING] [engine.py:2763:load_checkpoint] Unable to find latest file at /data/output/132node/checkpoints/latest, if trying to load latest checkpoint please ensure this file exists or pass an explicit checkpoint tag when loading a checkpoint.
WARNING: could not find the metadata file /data/output/132node/checkpoints 
    will not load any checkpoints and will start from random
[2024-04-03 22:03:12,132] [WARNING] [engine.py:2763:load_checkpoint] Unable to find latest file at /data/output/132node/checkpoints/latest, if trying to load latest checkpoint please ensure this file exists or pass an explicit checkpoint tag when loading a checkpoint.
[2024-04-03 22:03:12,133] [WARNING] [engine.py:2763:load_checkpoint] Unable to find latest file at /data/output/132node/checkpoints/latest, if trying to load latest checkpoint please ensure this file exists or pass an explicit checkpoint tag when loading a checkpoint.
[2024-04-03 22:03:12,133] [WARNING] [engine.py:2763:load_checkpoint] Unable to find latest file at /data/output/132node/checkpoints/latest, if trying to load latest checkpoint please ensure this file exists or pass an explicit checkpoint tag when loading a checkpoint.
[2024-04-03 22:03:12,133] [WARNING] [engine.py:2763:load_checkpoint] Unable to find latest file at /data/output/132node/checkpoints/latest, if trying to load latest checkpoint please ensure this file exists or pass an explicit checkpoint tag when loading a checkpoint.
[2024-04-03 22:03:12,133] [WARNING] [engine.py:2763:load_checkpoint] Unable to find latest file at /data/output/132node/checkpoints/latest, if trying to load latest checkpoint please ensure this file exists or pass an explicit checkpoint tag when loading a checkpoint.
[2024-04-03 22:03:12,133] [WARNING] [engine.py:2763:load_checkpoint] Unable to find latest file at /data/output/132node/checkpoints/latest, if trying to load latest checkpoint please ensure this file exists or pass an explicit checkpoint tag when loading a checkpoint.
[2024-04-03 22:03:12,133] [WARNING] [engine.py:2763:load_checkpoint] Unable to find latest file at /data/output/132node/checkpoints/latest, if trying to load latest checkpoint please ensure this file exists or pass an explicit checkpoint tag when loading a checkpoint.
time (ms) | load-checkpoint: 2.42
[after model, optimizer, and learning rate scheduler are built] datetime: 2024-04-03 22:03:12 
> building train, validation, and test datasets ...
 > datasets target sizes (minimum size):
    train:      2560000
    validation: 258560
    test:       2560
> building train, validation, and test datasets for GPT ...
Single data path provided for train, valid & test
 > building dataset index ...
    reading sizes...
    reading pointers...
    reading document index...
    creating numpy buffer of mmap...
    creating memory view of numpy buffer...
 > finished creating indexed dataset in 0.001090 seconds
    number of documents: 1558306
 > dataset split:
    train:
     document indices in [0, 1509999) total of 1509999 documents
    validation:
     document indices in [1509999, 1556748) total of 46749 documents
    test:
     document indices in [1556748, 1558306) total of 1558 documents
Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_doc_idx.npy
Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_doc_idx.npy
Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_doc_idx.npy
Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_doc_idx.npy
 > loaded doc-idx mapping from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_doc_idx.npy
Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_sample_idx.npy
Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_sample_idx.npy
Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_sample_idx.npy
Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_sample_idx.npy
 > loaded sample-idx mapping from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_sample_idx.npy
Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_shuffle_idx.npy
Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_shuffle_idx.npyLoading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_shuffle_idx.npy

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    total number of samples: 15244235
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> finished creating GPT datasets ...
time (ms) | model-and-optimizer-setup: 2860.75 | train/valid/test-data-iterators-setup: 1113.55
[after dataloaders are built] datetime: 2024-04-03 22:03:13 
done with setup ...
training ...
[before the start of training step] datetime: 2024-04-03 22:03:13 
[2024-04-03 22:08:15,101] [INFO] [logging.py:96:log_dist] [Rank 0] step=10, skipped=0, lr=[1.4999999999999998e-06, 1.4999999999999998e-06], mom=[(0.9, 0.95), (0.9, 0.95)]
steps: 10 loss: 11.4461 iter time (s): 30.238 samples/sec: 8.466
[Rank 0] (after 10 iterations) memory (MB) | allocated: 0.0 | max allocated: 0.0 | reserved: 0.0 | max reserved: 0.0
[Rank 1] (after 10 iterations) memory (MB) | allocated: 0.0 | max allocated: 0.0 | reserved: 0.0 | max reserved: 0.0
[Rank 4] (after 10 iterations) memory (MB) | allocated: 0.0 | max allocated: 0.0 | reserved: 0.0 | max reserved: 0.0
[Rank 5] (after 10 iterations) memory (MB) | allocated: 0.0 | max allocated: 0.0 | reserved: 0.0 | max reserved: 0.0
 iteration       10/   10000 | consumed samples:         2560 | consumed tokens:      5242880 | elapsed time per iteration (ms): 30185.1 | learning rate: 1.500E-06 | global batch size:   256 | lm loss: 1.177418E+01 | loss scale: 0.0 | grad norm: 13.481 | num zeros: 0.0 | number of skipped iterations:   0 | number of nan iterations:   0 | samples per second: 8.481 | TFLOPs: 177.37 |