Add files using upload-large-folder tool

132node/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

132node/log.txt

@@ -0,0 +1,1173 @@
+/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 ******************
+*************** 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 ******************
+*************** 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 ******************
+/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
+
+Loading dataset index file from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_shuffle_idx.npy
+ > loaded shuffle-idx mapping from /data/arxiv/tokenized_text_document_train_indexmap_2560000ns_2048sl_1234s_shuffle_idx.npy
+    loaded indexed file in 0.002 seconds
+    total number of samples: 15244235
+    total number of epochs: 1
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_doc_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_doc_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_doc_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_doc_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_sample_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_sample_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_sample_idx.npy
+ > loaded doc-idx mapping from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_doc_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_sample_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_shuffle_idx.npy > loaded sample-idx mapping from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_sample_idx.npy
+
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_shuffle_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_shuffle_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_shuffle_idx.npy
+ > loaded shuffle-idx mapping from /data/arxiv/tokenized_text_document_valid_indexmap_258560ns_2048sl_1234s_shuffle_idx.npy
+    loaded indexed file in 0.002 seconds
+    total number of samples: 481162
+    total number of epochs: 1
+Loading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_doc_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_doc_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_doc_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_doc_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_sample_idx.npyLoading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_sample_idx.npy
+
+Loading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_sample_idx.npy
+ > loaded doc-idx mapping from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_doc_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_sample_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_shuffle_idx.npy
+ > loaded sample-idx mapping from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_sample_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_shuffle_idx.npy
+Loading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_shuffle_idx.npyLoading dataset index file from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_shuffle_idx.npy
+
+ > loaded shuffle-idx mapping from /data/arxiv/tokenized_text_document_test_indexmap_2560ns_2048sl_1234s_shuffle_idx.npy
+    loaded indexed file in 0.001 seconds
+    total number of samples: 16581
+    total number of epochs: 1
+> 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 |

llama13b_5M/checkpoints_zero_stage_2/latest

@@ -0,0 +1 @@
+global_step0

llama13b_5M/checkpoints_zero_stage_2/latest_checkpointed_iteration.txt

@@ -0,0 +1 @@
+40

llama13b_5M/checkpoints_zero_stage_2/zero_to_fp32.py

@@ -0,0 +1,592 @@
+#!/usr/bin/env python
+
+# Copyright (c) Microsoft Corporation.
+# SPDX-License-Identifier: Apache-2.0
+
+# DeepSpeed Team
+
+# This script extracts fp32 consolidated weights from a zero 1, 2 and 3 DeepSpeed checkpoints. It gets
+# copied into the top level checkpoint dir, so the user can easily do the conversion at any point in
+# the future. Once extracted, the weights don't require DeepSpeed and can be used in any
+# application.
+#
+# example: python zero_to_fp32.py . pytorch_model.bin
+
+import argparse
+import torch
+import glob
+import math
+import os
+import re
+from collections import OrderedDict
+from dataclasses import dataclass
+
+# while this script doesn't use deepspeed to recover data, since the checkpoints are pickled with
+# DeepSpeed data structures it has to be available in the current python environment.
+from deepspeed.utils import logger
+from deepspeed.checkpoint.constants import (DS_VERSION, OPTIMIZER_STATE_DICT, SINGLE_PARTITION_OF_FP32_GROUPS,
+                                            FP32_FLAT_GROUPS, ZERO_STAGE, PARTITION_COUNT, PARAM_SHAPES, BUFFER_NAMES,
+                                            FROZEN_PARAM_SHAPES, FROZEN_PARAM_FRAGMENTS)
+
+
+@dataclass
+class zero_model_state:
+    buffers: dict()
+    param_shapes: dict()
+    shared_params: list
+    ds_version: int
+    frozen_param_shapes: dict()
+    frozen_param_fragments: dict()
+
+
+debug = 0
+
+# load to cpu
+device = torch.device('cpu')
+
+
+def atoi(text):
+    return int(text) if text.isdigit() else text
+
+
+def natural_keys(text):
+    '''
+    alist.sort(key=natural_keys) sorts in human order
+    http://nedbatchelder.com/blog/200712/human_sorting.html
+    (See Toothy's implementation in the comments)
+    '''
+    return [atoi(c) for c in re.split(r'(\d+)', text)]
+
+
+def get_model_state_file(checkpoint_dir, zero_stage):
+    if not os.path.isdir(checkpoint_dir):
+        raise FileNotFoundError(f"Directory '{checkpoint_dir}' doesn't exist")
+
+    # there should be only one file
+    if zero_stage <= 2:
+        file = os.path.join(checkpoint_dir, "mp_rank_00_model_states.pt")
+    elif zero_stage == 3:
+        file = os.path.join(checkpoint_dir, "zero_pp_rank_0_mp_rank_00_model_states.pt")
+
+    if not os.path.exists(file):
+        raise FileNotFoundError(f"can't find model states file at '{file}'")
+
+    return file
+
+
+def get_checkpoint_files(checkpoint_dir, glob_pattern):
+    # XXX: need to test that this simple glob rule works for multi-node setup too
+    ckpt_files = sorted(glob.glob(os.path.join(checkpoint_dir, glob_pattern)), key=natural_keys)
+
+    if len(ckpt_files) == 0:
+        raise FileNotFoundError(f"can't find {glob_pattern} files in directory '{checkpoint_dir}'")
+
+    return ckpt_files
+
+
+def get_optim_files(checkpoint_dir):
+    return get_checkpoint_files(checkpoint_dir, "*_optim_states.pt")
+
+
+def get_model_state_files(checkpoint_dir):
+    return get_checkpoint_files(checkpoint_dir, "*_model_states.pt")
+
+
+def parse_model_states(files):
+    zero_model_states = []
+    for file in files:
+        state_dict = torch.load(file, map_location=device)
+
+        if BUFFER_NAMES not in state_dict:
+            raise ValueError(f"{file} is not a model state checkpoint")
+        buffer_names = state_dict[BUFFER_NAMES]
+        if debug:
+            print("Found buffers:", buffer_names)
+
+        # recover just the buffers while restoring them to fp32 if they were saved in fp16
+        buffers = {k: v.float() for k, v in state_dict["module"].items() if k in buffer_names}
+        param_shapes = state_dict[PARAM_SHAPES]
+
+        # collect parameters that are included in param_shapes
+        param_names = []
+        for s in param_shapes:
+            for name in s.keys():
+                param_names.append(name)
+
+        # update with frozen parameters
+        frozen_param_shapes = state_dict.get(FROZEN_PARAM_SHAPES, None)
+        if frozen_param_shapes is not None:
+            if debug:
+                print(f"Found frozen_param_shapes: {frozen_param_shapes}")
+            param_names += list(frozen_param_shapes.keys())
+
+        # handle shared params
+        shared_params = [[k, v] for k, v in state_dict["shared_params"].items()]
+
+        ds_version = state_dict.get(DS_VERSION, None)
+
+        frozen_param_fragments = state_dict.get(FROZEN_PARAM_FRAGMENTS, None)
+
+        z_model_state = zero_model_state(buffers=buffers,
+                                         param_shapes=param_shapes,
+                                         shared_params=shared_params,
+                                         ds_version=ds_version,
+                                         frozen_param_shapes=frozen_param_shapes,
+                                         frozen_param_fragments=frozen_param_fragments)
+        zero_model_states.append(z_model_state)
+
+    return zero_model_states
+
+
+def parse_optim_states(files, ds_checkpoint_dir):
+
+    total_files = len(files)
+    state_dicts = []
+    for f in files:
+        state_dict = torch.load(f, map_location=device)
+        # immediately discard the potentially huge 2 optimizer states as we only care for fp32 master weights
+        # and also handle the case where it was already removed by another helper script
+        state_dict["optimizer_state_dict"].pop("optimizer_state_dict", None)
+        state_dicts.append(state_dict)
+
+    if not ZERO_STAGE in state_dicts[0][OPTIMIZER_STATE_DICT]:
+        raise ValueError(f"{files[0]} is not a zero checkpoint")
+    zero_stage = state_dicts[0][OPTIMIZER_STATE_DICT][ZERO_STAGE]
+    world_size = state_dicts[0][OPTIMIZER_STATE_DICT][PARTITION_COUNT]
+
+    # For ZeRO-2 each param group can have different partition_count as data parallelism for expert
+    # parameters can be different from data parallelism for non-expert parameters. So we can just
+    # use the max of the partition_count to get the dp world_size.
+
+    if type(world_size) is list:
+        world_size = max(world_size)
+
+    if world_size != total_files:
+        raise ValueError(
+            f"Expected {world_size} of '*_optim_states.pt' under '{ds_checkpoint_dir}' but found {total_files} files. "
+            "Possibly due to an overwrite of an old checkpoint, or a checkpoint didn't get saved by one or more processes."
+        )
+
+    # the groups are named differently in each stage
+    if zero_stage <= 2:
+        fp32_groups_key = SINGLE_PARTITION_OF_FP32_GROUPS
+    elif zero_stage == 3:
+        fp32_groups_key = FP32_FLAT_GROUPS
+    else:
+        raise ValueError(f"unknown zero stage {zero_stage}")
+
+    if zero_stage <= 2:
+        fp32_flat_groups = [state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key] for i in range(len(state_dicts))]
+    elif zero_stage == 3:
+        # if there is more than one param group, there will be multiple flattened tensors - one
+        # flattened tensor per group - for simplicity merge them into a single tensor
+        #
+        # XXX: could make the script more memory efficient for when there are multiple groups - it
+        # will require matching the sub-lists of param_shapes for each param group flattened tensor
+
+        fp32_flat_groups = [
+            torch.cat(state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key], 0) for i in range(len(state_dicts))
+        ]
+
+    return zero_stage, world_size, fp32_flat_groups
+
+
+def _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir):
+    """
+    Returns fp32 state_dict reconstructed from ds checkpoint
+
+    Args:
+        - ``ds_checkpoint_dir``: path to the deepspeed checkpoint folder (where the optimizer files are)
+
+    """
+    print(f"Processing zero checkpoint '{ds_checkpoint_dir}'")
+
+    optim_files = get_optim_files(ds_checkpoint_dir)
+    zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir)
+    print(f"Detected checkpoint of type zero stage {zero_stage}, world_size: {world_size}")
+
+    model_files = get_model_state_files(ds_checkpoint_dir)
+
+    zero_model_states = parse_model_states(model_files)
+    print(f'Parsing checkpoint created by deepspeed=={zero_model_states[0].ds_version}')
+
+    if zero_stage <= 2:
+        return _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states)
+    elif zero_stage == 3:
+        return _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states)
+
+
+def _zero2_merge_frozen_params(state_dict, zero_model_states):
+    if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
+        return
+
+    frozen_param_shapes = zero_model_states[0].frozen_param_shapes
+    frozen_param_fragments = zero_model_states[0].frozen_param_fragments
+
+    if debug:
+        num_elem = sum(s.numel() for s in frozen_param_shapes.values())
+        print(f'rank 0: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
+
+        wanted_params = len(frozen_param_shapes)
+        wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
+        avail_numel = sum([p.numel() for p in frozen_param_fragments.values()])
+        print(f'Frozen params: Have {avail_numel} numels to process.')
+        print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
+
+    total_params = 0
+    total_numel = 0
+    for name, shape in frozen_param_shapes.items():
+        total_params += 1
+        unpartitioned_numel = shape.numel()
+        total_numel += unpartitioned_numel
+
+        state_dict[name] = frozen_param_fragments[name]
+
+        if debug:
+            print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
+
+    print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _has_callable(obj, fn):
+    attr = getattr(obj, fn, None)
+    return callable(attr)
+
+
+def _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
+    param_shapes = zero_model_states[0].param_shapes
+
+    # Reconstruction protocol:
+    #
+    # XXX: document this
+
+    if debug:
+        for i in range(world_size):
+            for j in range(len(fp32_flat_groups[0])):
+                print(f"{FP32_FLAT_GROUPS}[{i}][{j}].shape={fp32_flat_groups[i][j].shape}")
+
+    # XXX: memory usage doubles here (zero2)
+    num_param_groups = len(fp32_flat_groups[0])
+    merged_single_partition_of_fp32_groups = []
+    for i in range(num_param_groups):
+        merged_partitions = [sd[i] for sd in fp32_flat_groups]
+        full_single_fp32_vector = torch.cat(merged_partitions, 0)
+        merged_single_partition_of_fp32_groups.append(full_single_fp32_vector)
+    avail_numel = sum(
+        [full_single_fp32_vector.numel() for full_single_fp32_vector in merged_single_partition_of_fp32_groups])
+
+    if debug:
+        wanted_params = sum([len(shapes) for shapes in param_shapes])
+        wanted_numel = sum([sum(shape.numel() for shape in shapes.values()) for shapes in param_shapes])
+        # not asserting if there is a mismatch due to possible padding
+        print(f"Have {avail_numel} numels to process.")
+        print(f"Need {wanted_numel} numels in {wanted_params} params.")
+
+    # params
+    # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
+    # out-of-core computing solution
+    total_numel = 0
+    total_params = 0
+    for shapes, full_single_fp32_vector in zip(param_shapes, merged_single_partition_of_fp32_groups):
+        offset = 0
+        avail_numel = full_single_fp32_vector.numel()
+        for name, shape in shapes.items():
+
+            unpartitioned_numel = shape.numel() if _has_callable(shape, 'numel') else math.prod(shape)
+            total_numel += unpartitioned_numel
+            total_params += 1
+
+            if debug:
+                print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
+            state_dict[name] = full_single_fp32_vector.narrow(0, offset, unpartitioned_numel).view(shape)
+            offset += unpartitioned_numel
+
+        # Z2 started to align to 2*world_size to improve nccl performance. Therefore both offset and
+        # avail_numel can differ by anywhere between 0..2*world_size. Due to two unrelated complex
+        # paddings performed in the code it's almost impossible to predict the exact numbers w/o the
+        # live optimizer object, so we are checking that the numbers are within the right range
+        align_to = 2 * world_size
+
+        def zero2_align(x):
+            return align_to * math.ceil(x / align_to)
+
+        if debug:
+            print(f"original offset={offset}, avail_numel={avail_numel}")
+
+        offset = zero2_align(offset)
+        avail_numel = zero2_align(avail_numel)
+
+        if debug:
+            print(f"aligned  offset={offset}, avail_numel={avail_numel}")
+
+        # Sanity check
+        if offset != avail_numel:
+            raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
+
+    print(f"Reconstructed fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states):
+    state_dict = OrderedDict()
+
+    # buffers
+    buffers = zero_model_states[0].buffers
+    state_dict.update(buffers)
+    if debug:
+        print(f"added {len(buffers)} buffers")
+
+    _zero2_merge_frozen_params(state_dict, zero_model_states)
+
+    _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
+
+    # recover shared parameters
+    for pair in zero_model_states[0].shared_params:
+        if pair[1] in state_dict:
+            state_dict[pair[0]] = state_dict[pair[1]]
+
+    return state_dict
+
+
+def zero3_partitioned_param_info(unpartitioned_numel, world_size):
+    remainder = unpartitioned_numel % world_size
+    padding_numel = (world_size - remainder) if remainder else 0
+    partitioned_numel = math.ceil(unpartitioned_numel / world_size)
+    return partitioned_numel, padding_numel
+
+
+def _zero3_merge_frozen_params(state_dict, world_size, zero_model_states):
+    if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
+        return
+
+    if debug:
+        for i in range(world_size):
+            num_elem = sum(s.numel() for s in zero_model_states[i].frozen_param_fragments.values())
+            print(f'rank {i}: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
+
+        frozen_param_shapes = zero_model_states[0].frozen_param_shapes
+        wanted_params = len(frozen_param_shapes)
+        wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
+        avail_numel = sum([p.numel() for p in zero_model_states[0].frozen_param_fragments.values()]) * world_size
+        print(f'Frozen params: Have {avail_numel} numels to process.')
+        print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
+
+    total_params = 0
+    total_numel = 0
+    for name, shape in zero_model_states[0].frozen_param_shapes.items():
+        total_params += 1
+        unpartitioned_numel = shape.numel()
+        total_numel += unpartitioned_numel
+
+        param_frags = tuple(model_state.frozen_param_fragments[name] for model_state in zero_model_states)
+        state_dict[name] = torch.cat(param_frags, 0).narrow(0, 0, unpartitioned_numel).view(shape)
+
+        partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
+
+        if debug:
+            print(
+                f"Frozen params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
+            )
+
+    print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
+    param_shapes = zero_model_states[0].param_shapes
+    avail_numel = fp32_flat_groups[0].numel() * world_size
+    # Reconstruction protocol: For zero3 we need to zip the partitions together at boundary of each
+    # param, re-consolidating each param, while dealing with padding if any
+
+    # merge list of dicts, preserving order
+    param_shapes = {k: v for d in param_shapes for k, v in d.items()}
+
+    if debug:
+        for i in range(world_size):
+            print(f"{FP32_FLAT_GROUPS}[{i}].shape={fp32_flat_groups[i].shape}")
+
+        wanted_params = len(param_shapes)
+        wanted_numel = sum(shape.numel() for shape in param_shapes.values())
+        # not asserting if there is a mismatch due to possible padding
+        avail_numel = fp32_flat_groups[0].numel() * world_size
+        print(f"Trainable params: Have {avail_numel} numels to process.")
+        print(f"Trainable params: Need {wanted_numel} numels in {wanted_params} params.")
+
+    # params
+    # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
+    # out-of-core computing solution
+    offset = 0
+    total_numel = 0
+    total_params = 0
+    for name, shape in param_shapes.items():
+
+        unpartitioned_numel = shape.numel()
+        total_numel += unpartitioned_numel
+        total_params += 1
+
+        partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
+
+        if debug:
+            print(
+                f"Trainable params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
+            )
+
+        # XXX: memory usage doubles here
+        state_dict[name] = torch.cat(
+            tuple(fp32_flat_groups[i].narrow(0, offset, partitioned_numel) for i in range(world_size)),
+            0).narrow(0, 0, unpartitioned_numel).view(shape)
+        offset += partitioned_numel
+
+    offset *= world_size
+
+    # Sanity check
+    if offset != avail_numel:
+        raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
+
+    print(f"Reconstructed Trainable fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states):
+    state_dict = OrderedDict()
+
+    # buffers
+    buffers = zero_model_states[0].buffers
+    state_dict.update(buffers)
+    if debug:
+        print(f"added {len(buffers)} buffers")
+
+    _zero3_merge_frozen_params(state_dict, world_size, zero_model_states)
+
+    _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
+
+    # recover shared parameters
+    for pair in zero_model_states[0].shared_params:
+        if pair[1] in state_dict:
+            state_dict[pair[0]] = state_dict[pair[1]]
+
+    return state_dict
+
+
+def get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag=None):
+    """
+    Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated state_dict that can be loaded with
+    ``load_state_dict()`` and used for training without DeepSpeed or shared with others, for example
+    via a model hub.
+
+    Args:
+        - ``checkpoint_dir``: path to the desired checkpoint folder
+        - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in 'latest' file. e.g., ``global_step14``
+
+    Returns:
+        - pytorch ``state_dict``
+
+    Note: this approach may not work if your application doesn't have sufficient free CPU memory and
+    you may need to use the offline approach using the ``zero_to_fp32.py`` script that is saved with
+    the checkpoint.
+
+    A typical usage might be ::
+
+        from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint
+        # do the training and checkpoint saving
+        state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir) # already on cpu
+        model = model.cpu() # move to cpu
+        model.load_state_dict(state_dict)
+        # submit to model hub or save the model to share with others
+
+    In this example the ``model`` will no longer be usable in the deepspeed context of the same
+    application. i.e. you will need to re-initialize the deepspeed engine, since
+    ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
+
+    If you want it all done for you, use ``load_state_dict_from_zero_checkpoint`` instead.
+
+    """
+    if tag is None:
+        latest_path = os.path.join(checkpoint_dir, 'latest')
+        if os.path.isfile(latest_path):
+            with open(latest_path, 'r') as fd:
+                tag = fd.read().strip()
+        else:
+            raise ValueError(f"Unable to find 'latest' file at {latest_path}")
+
+    ds_checkpoint_dir = os.path.join(checkpoint_dir, tag)
+
+    if not os.path.isdir(ds_checkpoint_dir):
+        raise FileNotFoundError(f"Directory '{ds_checkpoint_dir}' doesn't exist")
+
+    return _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir)
+
+
+def convert_zero_checkpoint_to_fp32_state_dict(checkpoint_dir, output_file, tag=None):
+    """
+    Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` file that can be
+    loaded with ``torch.load(file)`` + ``load_state_dict()`` and used for training without DeepSpeed.
+
+    Args:
+        - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
+        - ``output_file``: path to the pytorch fp32 state_dict output file (e.g. path/pytorch_model.bin)
+        - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
+    """
+
+    state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
+    print(f"Saving fp32 state dict to {output_file}")
+    torch.save(state_dict, output_file)
+
+
+def load_state_dict_from_zero_checkpoint(model, checkpoint_dir, tag=None):
+    """
+    1. Put the provided model to cpu
+    2. Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict``
+    3. Load it into the provided model
+
+    Args:
+        - ``model``: the model object to update
+        - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
+        - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
+
+    Returns:
+        - ``model`: modified model
+
+    Make sure you have plenty of CPU memory available before you call this function. If you don't
+    have enough use the ``zero_to_fp32.py`` utility to do the conversion. You will find it
+    conveniently placed for you in the checkpoint folder.
+
+    A typical usage might be ::
+
+        from deepspeed.utils.zero_to_fp32 import load_state_dict_from_zero_checkpoint
+        model = load_state_dict_from_zero_checkpoint(trainer.model, checkpoint_dir)
+        # submit to model hub or save the model to share with others
+
+    Note, that once this was run, the ``model`` will no longer be usable in the deepspeed context
+    of the same application. i.e. you will need to re-initialize the deepspeed engine, since
+    ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
+
+    """
+    logger.info(f"Extracting fp32 weights")
+    state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
+
+    logger.info(f"Overwriting model with fp32 weights")
+    model = model.cpu()
+    model.load_state_dict(state_dict, strict=False)
+
+    return model
+
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("checkpoint_dir",
+                        type=str,
+                        help="path to the desired checkpoint folder, e.g., path/checkpoint-12")
+    parser.add_argument(
+        "output_file",
+        type=str,
+        help="path to the pytorch fp32 state_dict output file (e.g. path/checkpoint-12/pytorch_model.bin)")
+    parser.add_argument("-t",
+                        "--tag",
+                        type=str,
+                        default=None,
+                        help="checkpoint tag used as a unique identifier for checkpoint. e.g., global_step1")
+    parser.add_argument("-d", "--debug", action='store_true', help="enable debug")
+    args = parser.parse_args()
+
+    debug = args.debug
+
+    convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir, args.output_file, tag=args.tag)

llama13b_5M/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:15:33/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:15:33/log.txt

@@ -0,0 +1,192 @@
+/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(
+[2024-05-13 09:15:34,948] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-05-13 09:15:36,265] [INFO] [runner.py:574:main] deepspeed_env file = /root/.deepspeed_env
+[2024-05-13 09:15:36,266] [INFO] [multinode_runner.py:72:get_cmd] Running on the following workers: 100.83.37.175,100.83.37.188
+[2024-05-13 09:15:36,266] [INFO] [runner.py:585:main] cmd = pdsh -S -f 1024 -w 100.83.37.175,100.83.37.188 export PYTHONPATH=/Model-References/PyTorch/common:/usr/lib/habanalabs/:$PYTHONPATH; export PYTHON=/usr/bin/python3; export PT_HPU_LAZY_ACC_PAR_MODE=0; export PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES=0; export PT_HPU_ENABLE_WEIGHT_CPU_PERMUTE=0; export MODEL_REFERENCES_ROOT=/Model-References; export ENABLE_CONSOLE=false; export LOG_LEVEL_ALL=4;  cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed; /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMzcuMTc1IjogWzAsIDEsIDIsIDMsIDQsIDUsIDYsIDddLCAiMTAwLjgzLjM3LjE4OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --node_rank=%n --master_addr=100.83.37.175 --master_port=29500 --no_python --no_local_rank /usr/bin/bash -c '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:15:33/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:15:33/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:15:33/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/llama13b_multiling_800M/13-05-2024-09:15:33/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:15:33/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'
+100.83.37.175: Warning: Permanently added '[100.83.37.175]:3122' (ED25519) to the list of known hosts.
+100.83.37.188: Warning: Permanently added '[100.83.37.188]:3122' (ED25519) to the list of known hosts.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:15:37,925] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:15:37,963] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:15:39,161] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.188: [2024-05-13 09:15:39,161] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=1
+100.83.37.188: [2024-05-13 09:15:39,161] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.188: [2024-05-13 09:15:39,161] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.188: [2024-05-13 09:15:39,161] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.175: [2024-05-13 09:15:39,324] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.175: [2024-05-13 09:15:39,324] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=0
+100.83.37.175: [2024-05-13 09:15:39,324] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.175: [2024-05-13 09:15:39,324] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.175: [2024-05-13 09:15:39,324] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188: [2024-05-13 09:15:40,973] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:15:40,973] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:15:40,982] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:15:41,032] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.175: [2024-05-13 09:15:41,048] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:15:41,067] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:15:41,099] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:15:41,106] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:15:41,108] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:15:41,111] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:15:41,117] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:15:41,139] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:15:41,145] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:15:41,147] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:15:41,152] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.188: [2024-05-13 09:15:41,183] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe    
+100.83.37.188: from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: ImportErrorcannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: : cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: [2024-05-13 09:15:43,168] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 115299
+100.83.37.188: [2024-05-13 09:15:43,170] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 115300
+100.83.37.188: [2024-05-13 09:15:43,170] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 115301
+100.83.37.188: [2024-05-13 09:15:43,170] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 115302
+100.83.37.188: [2024-05-13 09:15:43,171] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 115303
+100.83.37.188: [2024-05-13 09:15:43,171] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 115304
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: [2024-05-13 09:15:43,198] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 115305
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: [2024-05-13 09:15:43,251] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 115306
+100.83.37.188: [2024-05-13 09:15:43,252] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:15:33/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:15:33/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:15:33/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/llama13b_multiling_800M/13-05-2024-09:15:33/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:15:33/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+100.83.37.175: [2024-05-13 09:15:43,331] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 19210
+100.83.37.175: [2024-05-13 09:15:43,386] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 19211
+100.83.37.175: [2024-05-13 09:15:43,386] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 19212
+100.83.37.175: [2024-05-13 09:15:43,413] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 19213
+100.83.37.175: [2024-05-13 09:15:43,414] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 19214
+100.83.37.175: [2024-05-13 09:15:43,442] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 19218
+100.83.37.175: [2024-05-13 09:15:43,494] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 19221
+100.83.37.175: [2024-05-13 09:15:43,495] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 19225
+100.83.37.175: [2024-05-13 09:15:43,522] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:15:33/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:15:33/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:15:33/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/llama13b_multiling_800M/13-05-2024-09:15:33/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:15:33/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.188: ssh exited with exit code 1
+pdsh@vizzhy-150-3: 100.83.37.175: ssh exited with exit code 1

llama13b_multiling_800M/13-05-2024-09:15:33/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-09:17:37/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:17:37/log.txt

@@ -0,0 +1,192 @@
+/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(
+[2024-05-13 09:17:39,563] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-05-13 09:17:40,878] [INFO] [runner.py:574:main] deepspeed_env file = /root/.deepspeed_env
+[2024-05-13 09:17:40,878] [INFO] [multinode_runner.py:72:get_cmd] Running on the following workers: 100.83.37.175,100.83.37.188
+[2024-05-13 09:17:40,878] [INFO] [runner.py:585:main] cmd = pdsh -S -f 1024 -w 100.83.37.175,100.83.37.188 export PYTHONPATH=/Model-References/PyTorch/common:/usr/lib/habanalabs/:$PYTHONPATH; export PYTHON=/usr/bin/python3; export PT_HPU_LAZY_ACC_PAR_MODE=0; export PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES=0; export PT_HPU_ENABLE_WEIGHT_CPU_PERMUTE=0; export MODEL_REFERENCES_ROOT=/Model-References; export ENABLE_CONSOLE=false; export LOG_LEVEL_ALL=4;  cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed; /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMzcuMTc1IjogWzAsIDEsIDIsIDMsIDQsIDUsIDYsIDddLCAiMTAwLjgzLjM3LjE4OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --node_rank=%n --master_addr=100.83.37.175 --master_port=29500 --no_python --no_local_rank /usr/bin/bash -c '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:17:37/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:17:37/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:17:37/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/llama13b_multiling_800M/13-05-2024-09:17:37/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:17:37/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'
+100.83.37.188: Warning: Permanently added '[100.83.37.188]:3122' (ED25519) to the list of known hosts.
+100.83.37.175: Warning: Permanently added '[100.83.37.175]:3122' (ED25519) to the list of known hosts.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:17:42,581] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:17:42,604] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:17:43,708] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.188: [2024-05-13 09:17:43,709] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=1
+100.83.37.188: [2024-05-13 09:17:43,709] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.188: [2024-05-13 09:17:43,709] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.188: [2024-05-13 09:17:43,709] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.175: [2024-05-13 09:17:44,192] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.175: [2024-05-13 09:17:44,192] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=0
+100.83.37.175: [2024-05-13 09:17:44,192] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.175: [2024-05-13 09:17:44,192] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.175: [2024-05-13 09:17:44,192] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.188: [2024-05-13 09:17:45,563] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:17:45,570] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:17:45,591] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:17:45,601] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:17:45,602] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:17:45,653] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:17:45,657] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:17:45,693] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.175: [2024-05-13 09:17:45,897] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:17:45,898] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:17:45,908] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:17:45,958] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:17:46,008] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:17:46,041] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:17:46,042] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:17:46,045] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.188:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.188: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: [2024-05-13 09:17:47,715] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 116640
+100.83.37.188: [2024-05-13 09:17:47,717] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 116641
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: [2024-05-13 09:17:47,744] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 116642
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: [2024-05-13 09:17:47,771] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 116643
+100.83.37.188: [2024-05-13 09:17:47,771] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 116644
+100.83.37.188: [2024-05-13 09:17:47,772] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 116645
+100.83.37.188: [2024-05-13 09:17:47,799] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 116646
+100.83.37.188: [2024-05-13 09:17:47,799] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 116647
+100.83.37.188: [2024-05-13 09:17:47,826] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:17:37/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:17:37/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:17:37/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/llama13b_multiling_800M/13-05-2024-09:17:37/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:17:37/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 25, in <module>
+100.83.37.175:     from megatron.model import LLaMAModel, LLaMAModelPipe
+100.83.37.175: ImportError: cannot import name 'LLaMAModel' from 'megatron.model' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: [2024-05-13 09:17:48,200] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 20742
+100.83.37.175: [2024-05-13 09:17:48,201] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 20743
+pdsh@vizzhy-150-3: 100.83.37.188: ssh exited with exit code 1
+100.83.37.175: [2024-05-13 09:17:48,229] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 20744
+100.83.37.175: [2024-05-13 09:17:48,229] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 20745
+100.83.37.175: [2024-05-13 09:17:48,229] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 20749
+100.83.37.175: [2024-05-13 09:17:48,230] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 20753
+100.83.37.175: [2024-05-13 09:17:48,230] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 20755
+100.83.37.175: [2024-05-13 09:17:48,257] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 20760
+100.83.37.175: [2024-05-13 09:17:48,310] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:17:37/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:17:37/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:17:37/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/llama13b_multiling_800M/13-05-2024-09:17:37/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:17:37/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.175: ssh exited with exit code 1

llama13b_multiling_800M/13-05-2024-09:17:37/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-09:19:04/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:19:04/log.txt

@@ -0,0 +1,338 @@
+/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(
+[2024-05-13 09:19:05,899] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-05-13 09:19:07,222] [INFO] [runner.py:574:main] deepspeed_env file = /root/.deepspeed_env
+[2024-05-13 09:19:07,222] [INFO] [multinode_runner.py:72:get_cmd] Running on the following workers: 100.83.37.175,100.83.37.188
+[2024-05-13 09:19:07,222] [INFO] [runner.py:585:main] cmd = pdsh -S -f 1024 -w 100.83.37.175,100.83.37.188 export PYTHONPATH=/Model-References/PyTorch/common:/usr/lib/habanalabs/:$PYTHONPATH; export PYTHON=/usr/bin/python3; export PT_HPU_LAZY_ACC_PAR_MODE=0; export PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES=0; export PT_HPU_ENABLE_WEIGHT_CPU_PERMUTE=0; export MODEL_REFERENCES_ROOT=/Model-References; export ENABLE_CONSOLE=false; export LOG_LEVEL_ALL=4;  cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed; /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMzcuMTc1IjogWzAsIDEsIDIsIDMsIDQsIDUsIDYsIDddLCAiMTAwLjgzLjM3LjE4OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --node_rank=%n --master_addr=100.83.37.175 --master_port=29500 --no_python --no_local_rank /usr/bin/bash -c '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:19:04/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:19:04/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:19:04/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/llama13b_multiling_800M/13-05-2024-09:19:04/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:19:04/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'
+100.83.37.175: Warning: Permanently added '[100.83.37.175]:3122' (ED25519) to the list of known hosts.
+100.83.37.188: Warning: Permanently added '[100.83.37.188]:3122' (ED25519) to the list of known hosts.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:19:08,928] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:19:08,948] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:19:10,060] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.188: [2024-05-13 09:19:10,061] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=1
+100.83.37.188: [2024-05-13 09:19:10,061] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.188: [2024-05-13 09:19:10,061] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.188: [2024-05-13 09:19:10,061] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.175: [2024-05-13 09:19:10,515] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.175: [2024-05-13 09:19:10,515] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=0
+100.83.37.175: [2024-05-13 09:19:10,515] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.175: [2024-05-13 09:19:10,515] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.175: [2024-05-13 09:19:10,515] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.188: [2024-05-13 09:19:11,871] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:19:11,885] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:19:11,891] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:19:11,941] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:19:11,983] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:19:11,989] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:19:11,991] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:19:11,998] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:19:12,271] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:19:12,293] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:19:12,303] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:19:12,347] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:19:12,348] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:19:12,356] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:19:12,379] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:19:12,820] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.188:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.188: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.188:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.188: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.188:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.188: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.188:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.188: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.188:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.188: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.188:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.188: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.188:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.188: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.188:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.188: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.175:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.175: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.188: [2024-05-13 09:19:14,067] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 117981
+100.83.37.188: [2024-05-13 09:19:14,069] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 117982
+100.83.37.188: [2024-05-13 09:19:14,069] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 117983
+100.83.37.188: [2024-05-13 09:19:14,069] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 117984
+100.83.37.188: [2024-05-13 09:19:14,070] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 117985
+100.83.37.188: [2024-05-13 09:19:14,070] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 117986
+100.83.37.188: [2024-05-13 09:19:14,070] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 117987
+100.83.37.188: [2024-05-13 09:19:14,070] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 117988
+100.83.37.188: [2024-05-13 09:19:14,071] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:19:04/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:19:04/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:19:04/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/llama13b_multiling_800M/13-05-2024-09:19:04/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:19:04/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.175:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.175: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.175:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.175: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.175:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.175: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.175:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.175: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+pdsh@vizzhy-150-3: 100.83.37.188: ssh exited with exit code 1
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.175:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.175: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 29, in <module>
+100.83.37.175:     from .utils import init_method_normal, scaled_init_method_normal, WrapName
+100.83.37.175: ImportError: cannot import name 'WrapName' from 'megatron.model.utils' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/utils.py)
+100.83.37.175: [2024-05-13 09:19:14,523] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 22272
+100.83.37.175: [2024-05-13 09:19:14,551] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 22273
+100.83.37.175: [2024-05-13 09:19:14,551] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 22274
+100.83.37.175: [2024-05-13 09:19:14,605] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 22275
+100.83.37.175: [2024-05-13 09:19:14,632] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 22276
+100.83.37.175: [2024-05-13 09:19:14,685] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 22280
+100.83.37.175: [2024-05-13 09:19:14,686] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 22286
+100.83.37.175: [2024-05-13 09:19:14,738] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 22288
+100.83.37.175: [2024-05-13 09:19:14,739] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:19:04/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:19:04/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:19:04/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/llama13b_multiling_800M/13-05-2024-09:19:04/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:19:04/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.175: ssh exited with exit code 1

llama13b_multiling_800M/13-05-2024-09:19:04/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-09:21:14/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:21:14/log.txt

@@ -0,0 +1,352 @@
+/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(
+[2024-05-13 09:21:16,057] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-05-13 09:21:17,379] [INFO] [runner.py:574:main] deepspeed_env file = /root/.deepspeed_env
+[2024-05-13 09:21:17,380] [INFO] [multinode_runner.py:72:get_cmd] Running on the following workers: 100.83.37.175,100.83.37.188
+[2024-05-13 09:21:17,380] [INFO] [runner.py:585:main] cmd = pdsh -S -f 1024 -w 100.83.37.175,100.83.37.188 export PYTHONPATH=/Model-References/PyTorch/common:/usr/lib/habanalabs/:$PYTHONPATH; export PYTHON=/usr/bin/python3; export PT_HPU_LAZY_ACC_PAR_MODE=0; export PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES=0; export PT_HPU_ENABLE_WEIGHT_CPU_PERMUTE=0; export MODEL_REFERENCES_ROOT=/Model-References; export ENABLE_CONSOLE=false; export LOG_LEVEL_ALL=4;  cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed; /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMzcuMTc1IjogWzAsIDEsIDIsIDMsIDQsIDUsIDYsIDddLCAiMTAwLjgzLjM3LjE4OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --node_rank=%n --master_addr=100.83.37.175 --master_port=29500 --no_python --no_local_rank /usr/bin/bash -c '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:21:14/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:21:14/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:21:14/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/llama13b_multiling_800M/13-05-2024-09:21:14/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:21:14/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'
+100.83.37.175: Warning: Permanently added '[100.83.37.175]:3122' (ED25519) to the list of known hosts.
+100.83.37.188: Warning: Permanently added '[100.83.37.188]:3122' (ED25519) to the list of known hosts.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:21:19,106] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:21:19,149] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:21:20,287] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.188: [2024-05-13 09:21:20,287] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=1
+100.83.37.188: [2024-05-13 09:21:20,287] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.188: [2024-05-13 09:21:20,287] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.188: [2024-05-13 09:21:20,287] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.175: [2024-05-13 09:21:20,675] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.175: [2024-05-13 09:21:20,675] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=0
+100.83.37.175: [2024-05-13 09:21:20,675] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.175: [2024-05-13 09:21:20,675] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.175: [2024-05-13 09:21:20,675] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.188: [2024-05-13 09:21:22,063] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:21:22,131] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:21:22,159] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:21:22,173] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:21:22,190] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:21:22,196] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:21:22,200] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:21:22,243] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.175: [2024-05-13 09:21:22,365] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:21:22,427] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:21:22,438] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:21:22,458] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:21:22,458] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:21:22,504] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:21:22,506] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:21:22,543] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: [2024-05-13 09:21:24,294] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 119322
+100.83.37.188: [2024-05-13 09:21:24,296] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 119323
+100.83.37.188: [2024-05-13 09:21:24,296] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 119324
+100.83.37.188: [2024-05-13 09:21:24,296] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 119325
+100.83.37.188: [2024-05-13 09:21:24,324] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 119326
+100.83.37.188: [2024-05-13 09:21:24,324] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 119327
+100.83.37.188: [2024-05-13 09:21:24,376] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 119328
+100.83.37.188: [2024-05-13 09:21:24,376] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 119329
+100.83.37.188: [2024-05-13 09:21:24,377] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:21:14/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:21:14/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:21:14/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/llama13b_multiling_800M/13-05-2024-09:21:14/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:21:14/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: [2024-05-13 09:21:24,683] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 23800
+100.83.37.175: [2024-05-13 09:21:24,685] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 23801
+pdsh@vizzhy-150-3: 100.83.37.188: ssh exited with exit code 1
+100.83.37.175: [2024-05-13 09:21:24,738] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 23802
+100.83.37.175: [2024-05-13 09:21:24,739] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 23803
+100.83.37.175: [2024-05-13 09:21:24,739] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 23807
+100.83.37.175: [2024-05-13 09:21:24,791] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 23810
+100.83.37.175: [2024-05-13 09:21:24,819] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 23813
+100.83.37.175: [2024-05-13 09:21:24,820] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 23816
+100.83.37.175: [2024-05-13 09:21:24,820] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:21:14/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:21:14/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:21:14/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/llama13b_multiling_800M/13-05-2024-09:21:14/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:21:14/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.175: ssh exited with exit code 1

llama13b_multiling_800M/13-05-2024-09:21:14/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-09:23:20/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:23:20/log.txt

@@ -0,0 +1,352 @@
+/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(
+[2024-05-13 09:23:22,419] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-05-13 09:23:23,730] [INFO] [runner.py:574:main] deepspeed_env file = /root/.deepspeed_env
+[2024-05-13 09:23:23,730] [INFO] [multinode_runner.py:72:get_cmd] Running on the following workers: 100.83.37.175,100.83.37.188
+[2024-05-13 09:23:23,730] [INFO] [runner.py:585:main] cmd = pdsh -S -f 1024 -w 100.83.37.175,100.83.37.188 export PYTHONPATH=/Model-References/PyTorch/common:/usr/lib/habanalabs/:$PYTHONPATH; export PYTHON=/usr/bin/python3; export PT_HPU_LAZY_ACC_PAR_MODE=0; export PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES=0; export PT_HPU_ENABLE_WEIGHT_CPU_PERMUTE=0; export MODEL_REFERENCES_ROOT=/Model-References; export ENABLE_CONSOLE=false; export LOG_LEVEL_ALL=4;  cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed; /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMzcuMTc1IjogWzAsIDEsIDIsIDMsIDQsIDUsIDYsIDddLCAiMTAwLjgzLjM3LjE4OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --node_rank=%n --master_addr=100.83.37.175 --master_port=29500 --no_python --no_local_rank /usr/bin/bash -c '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:23:20/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:23:20/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:23:20/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/llama13b_multiling_800M/13-05-2024-09:23:20/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:23:20/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'
+100.83.37.188: Warning: Permanently added '[100.83.37.188]:3122' (ED25519) to the list of known hosts.
+100.83.37.175: Warning: Permanently added '[100.83.37.175]:3122' (ED25519) to the list of known hosts.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:23:25,440] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:23:25,443] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:23:26,645] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.188: [2024-05-13 09:23:26,645] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=1
+100.83.37.188: [2024-05-13 09:23:26,645] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.188: [2024-05-13 09:23:26,645] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.188: [2024-05-13 09:23:26,645] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.175: [2024-05-13 09:23:26,998] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.175: [2024-05-13 09:23:26,998] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=0
+100.83.37.175: [2024-05-13 09:23:26,998] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.175: [2024-05-13 09:23:26,998] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.175: [2024-05-13 09:23:26,998] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188: [2024-05-13 09:23:28,463] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:23:28,476] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:23:28,493] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:23:28,493] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:23:28,495] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:23:28,533] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:23:28,545] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:23:28,551] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:23:28,740] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:23:28,745] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:23:28,747] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:23:28,759] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:23:28,795] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:23:28,838] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:23:28,838] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:23:29,024] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.188:     from megatron import get_args
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.188:     from .initialize  import initialize_megatron
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.188:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.188:     from megatron.model.utils import init_method_normal
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.188:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.188:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.188: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.188: [2024-05-13 09:23:30,652] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 120663
+100.83.37.188: [2024-05-13 09:23:30,654] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 120664
+100.83.37.188: [2024-05-13 09:23:30,654] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 120665
+100.83.37.188: [2024-05-13 09:23:30,654] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 120666
+100.83.37.188: [2024-05-13 09:23:30,655] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 120667
+100.83.37.188: [2024-05-13 09:23:30,655] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 120668
+100.83.37.188: [2024-05-13 09:23:30,655] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 120669
+100.83.37.188: [2024-05-13 09:23:30,655] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 120670
+100.83.37.188: [2024-05-13 09:23:30,656] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:23:20/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:23:20/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:23:20/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/llama13b_multiling_800M/13-05-2024-09:23:20/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:23:20/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: [2024-05-13 09:23:31,007] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 25330
+100.83.37.175: [2024-05-13 09:23:31,009] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 25331
+pdsh@vizzhy-150-3: 100.83.37.188: ssh exited with exit code 1
+100.83.37.175: [2024-05-13 09:23:31,036] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 25332
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 20, in <module>
+100.83.37.175:     from megatron import get_args
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/__init__.py", line 17, in <module>
+100.83.37.175:     from .initialize  import initialize_megatron
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 20, in <module>
+100.83.37.175:     from megatron.arguments import (parse_args, validate_args)
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/arguments.py", line 20, in <module>
+100.83.37.175:     from megatron.model.utils import init_method_normal
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py", line 16, in <module>
+100.83.37.175:     from .llama_model import LLaMAModel, LLaMAModelPipe
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/llama_model.py", line 32, in <module>
+100.83.37.175:     from megatron.model import RMSNorm, LayerNorm, CrossEntropy
+100.83.37.175: ImportError: cannot import name 'RMSNorm' from partially initialized module 'megatron.model' (most likely due to a circular import) (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/model/__init__.py)
+100.83.37.175: [2024-05-13 09:23:31,089] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 25333
+100.83.37.175: [2024-05-13 09:23:31,090] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 25337
+100.83.37.175: [2024-05-13 09:23:31,118] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 25340
+100.83.37.175: [2024-05-13 09:23:31,118] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 25344
+100.83.37.175: [2024-05-13 09:23:31,145] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 25348
+100.83.37.175: [2024-05-13 09:23:31,198] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:23:20/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:23:20/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:23:20/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/llama13b_multiling_800M/13-05-2024-09:23:20/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:23:20/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.175: ssh exited with exit code 1

llama13b_multiling_800M/13-05-2024-09:23:20/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-09:29:05/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:29:05/log.txt

@@ -0,0 +1,192 @@
+/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(
+[2024-05-13 09:29:06,726] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-05-13 09:29:08,058] [INFO] [runner.py:574:main] deepspeed_env file = /root/.deepspeed_env
+[2024-05-13 09:29:08,058] [INFO] [multinode_runner.py:72:get_cmd] Running on the following workers: 100.83.37.175,100.83.37.188
+[2024-05-13 09:29:08,058] [INFO] [runner.py:585:main] cmd = pdsh -S -f 1024 -w 100.83.37.175,100.83.37.188 export PYTHONPATH=/Model-References/PyTorch/common:/usr/lib/habanalabs/:$PYTHONPATH; export PYTHON=/usr/bin/python3; export PT_HPU_LAZY_ACC_PAR_MODE=0; export PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES=0; export PT_HPU_ENABLE_WEIGHT_CPU_PERMUTE=0; export MODEL_REFERENCES_ROOT=/Model-References; export ENABLE_CONSOLE=false; export LOG_LEVEL_ALL=4;  cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed; /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMzcuMTc1IjogWzAsIDEsIDIsIDMsIDQsIDUsIDYsIDddLCAiMTAwLjgzLjM3LjE4OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --node_rank=%n --master_addr=100.83.37.175 --master_port=29500 --no_python --no_local_rank /usr/bin/bash -c '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:29:05/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:29:05/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:29:05/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/llama13b_multiling_800M/13-05-2024-09:29:05/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:29:05/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'
+100.83.37.175: Warning: Permanently added '[100.83.37.175]:3122' (ED25519) to the list of known hosts.
+100.83.37.188: Warning: Permanently added '[100.83.37.188]:3122' (ED25519) to the list of known hosts.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:29:09,769] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:29:09,793] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:29:10,927] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.188: [2024-05-13 09:29:10,927] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=1
+100.83.37.188: [2024-05-13 09:29:10,927] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.188: [2024-05-13 09:29:10,927] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.188: [2024-05-13 09:29:10,927] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.175: [2024-05-13 09:29:11,349] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.175: [2024-05-13 09:29:11,349] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=0
+100.83.37.175: [2024-05-13 09:29:11,349] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.175: [2024-05-13 09:29:11,349] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.175: [2024-05-13 09:29:11,349] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.188: [2024-05-13 09:29:12,742] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:29:12,778] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:29:12,800] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:29:12,837] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:29:12,847] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:29:12,851] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:29:13,074] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:29:13,080] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.188: [2024-05-13 09:29:13,083] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:29:13,090] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:29:13,091] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:29:13,095] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:29:13,188] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:29:13,189] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:29:13,189] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:29:13,261] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:     from megatron.global_vars import get_current_device  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175: 
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: ImportErrorcannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: : cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: [2024-05-13 09:29:15,935] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 122004
+100.83.37.188: [2024-05-13 09:29:15,937] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 122005
+100.83.37.188: [2024-05-13 09:29:15,937] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 122006
+100.83.37.188: [2024-05-13 09:29:15,937] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 122007
+100.83.37.188: [2024-05-13 09:29:15,938] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 122008
+100.83.37.188: [2024-05-13 09:29:15,938] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 122009
+100.83.37.188: [2024-05-13 09:29:15,938] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 122010
+100.83.37.188: [2024-05-13 09:29:15,938] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 122011
+100.83.37.188: [2024-05-13 09:29:15,965] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:29:05/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:29:05/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:29:05/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/llama13b_multiling_800M/13-05-2024-09:29:05/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:29:05/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.188: ssh exited with exit code 1
+100.83.37.175: [2024-05-13 09:29:16,357] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 26867
+100.83.37.175: [2024-05-13 09:29:16,359] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 26868
+100.83.37.175: [2024-05-13 09:29:16,359] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 26869
+100.83.37.175: [2024-05-13 09:29:16,360] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 26870
+100.83.37.175: [2024-05-13 09:29:16,360] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 26873
+100.83.37.175: [2024-05-13 09:29:16,361] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 26875
+100.83.37.175: [2024-05-13 09:29:16,361] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 26877
+100.83.37.175: [2024-05-13 09:29:16,362] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 26878
+100.83.37.175: [2024-05-13 09:29:16,362] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:29:05/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:29:05/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:29:05/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/llama13b_multiling_800M/13-05-2024-09:29:05/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:29:05/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.175: ssh exited with exit code 1

llama13b_multiling_800M/13-05-2024-09:29:05/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-09:32:36/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:32:36/log.txt

@@ -0,0 +1,192 @@
+/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(
+[2024-05-13 09:32:38,292] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-05-13 09:32:39,628] [INFO] [runner.py:574:main] deepspeed_env file = /root/.deepspeed_env
+[2024-05-13 09:32:39,628] [INFO] [multinode_runner.py:72:get_cmd] Running on the following workers: 100.83.37.175,100.83.37.188
+[2024-05-13 09:32:39,628] [INFO] [runner.py:585:main] cmd = pdsh -S -f 1024 -w 100.83.37.175,100.83.37.188 export PYTHONPATH=/Model-References/PyTorch/common:/usr/lib/habanalabs/:$PYTHONPATH; export PYTHON=/usr/bin/python3; export PT_HPU_LAZY_ACC_PAR_MODE=0; export PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES=0; export PT_HPU_ENABLE_WEIGHT_CPU_PERMUTE=0; export MODEL_REFERENCES_ROOT=/Model-References; export ENABLE_CONSOLE=false; export LOG_LEVEL_ALL=4;  cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed; /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMzcuMTc1IjogWzAsIDEsIDIsIDMsIDQsIDUsIDYsIDddLCAiMTAwLjgzLjM3LjE4OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --node_rank=%n --master_addr=100.83.37.175 --master_port=29500 --no_python --no_local_rank /usr/bin/bash -c '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:32:36/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:32:36/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:32:36/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/llama13b_multiling_800M/13-05-2024-09:32:36/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:32:36/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'
+100.83.37.188: Warning: Permanently added '[100.83.37.188]:3122' (ED25519) to the list of known hosts.
+100.83.37.175: Warning: Permanently added '[100.83.37.175]:3122' (ED25519) to the list of known hosts.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:32:41,274] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:32:41,392] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:32:42,611] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.188: [2024-05-13 09:32:42,611] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=1
+100.83.37.188: [2024-05-13 09:32:42,611] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.188: [2024-05-13 09:32:42,611] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.188: [2024-05-13 09:32:42,611] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175: [2024-05-13 09:32:42,649] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.175: [2024-05-13 09:32:42,649] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=0
+100.83.37.175: [2024-05-13 09:32:42,649] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.175: [2024-05-13 09:32:42,649] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.175: [2024-05-13 09:32:42,649] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.175: [2024-05-13 09:32:44,388] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:32:44,393] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:32:44,401] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:32:44,405] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.188: [2024-05-13 09:32:44,411] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:32:44,416] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:32:44,423] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:32:44,476] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:32:44,478] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:32:44,496] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.175: [2024-05-13 09:32:44,546] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:32:44,557] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:32:44,575] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:32:44,602] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:32:44,603] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:32:44,606] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: ImportErrorcannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py): 
+100.83.37.188: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.188:     from megatron.global_vars import get_current_device
+100.83.37.188: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 27, in <module>
+100.83.37.175:     from megatron.global_vars import get_current_device
+100.83.37.175: ImportError: cannot import name 'get_current_device' from 'megatron.global_vars' (/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/global_vars.py)
+100.83.37.188: [2024-05-13 09:32:47,619] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 123369
+100.83.37.188: [2024-05-13 09:32:47,620] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 123370
+100.83.37.188: [2024-05-13 09:32:47,621] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 123371
+100.83.37.188: [2024-05-13 09:32:47,621] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 123372
+100.83.37.188: [2024-05-13 09:32:47,621] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 123373
+100.83.37.188: [2024-05-13 09:32:47,621] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 123374
+100.83.37.188: [2024-05-13 09:32:47,621] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 123375
+100.83.37.188: [2024-05-13 09:32:47,622] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 123376
+100.83.37.188: [2024-05-13 09:32:47,622] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:32:36/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:32:36/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:32:36/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/llama13b_multiling_800M/13-05-2024-09:32:36/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:32:36/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+100.83.37.175: [2024-05-13 09:32:47,658] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 28420
+100.83.37.175: [2024-05-13 09:32:47,659] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 28421
+100.83.37.175: [2024-05-13 09:32:47,660] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 28422
+100.83.37.175: [2024-05-13 09:32:47,660] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 28423
+100.83.37.175: [2024-05-13 09:32:47,661] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 28427
+100.83.37.175: [2024-05-13 09:32:47,661] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 28432
+100.83.37.175: [2024-05-13 09:32:47,661] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 28435
+100.83.37.175: [2024-05-13 09:32:47,662] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 28441
+100.83.37.175: [2024-05-13 09:32:47,662] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:32:36/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:32:36/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:32:36/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/llama13b_multiling_800M/13-05-2024-09:32:36/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:32:36/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.175: ssh exited with exit code 1
+pdsh@vizzhy-150-3: 100.83.37.188: ssh exited with exit code 1

llama13b_multiling_800M/13-05-2024-09:32:36/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-09:34:09/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:34:09/log.txt

@@ -0,0 +1,656 @@
+/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(
+[2024-05-13 09:34:11,123] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-05-13 09:34:12,433] [INFO] [runner.py:574:main] deepspeed_env file = /root/.deepspeed_env
+[2024-05-13 09:34:12,434] [INFO] [multinode_runner.py:72:get_cmd] Running on the following workers: 100.83.37.175,100.83.37.188
+[2024-05-13 09:34:12,434] [INFO] [runner.py:585:main] cmd = pdsh -S -f 1024 -w 100.83.37.175,100.83.37.188 export PYTHONPATH=/Model-References/PyTorch/common:/usr/lib/habanalabs/:$PYTHONPATH; export PYTHON=/usr/bin/python3; export PT_HPU_LAZY_ACC_PAR_MODE=0; export PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES=0; export PT_HPU_ENABLE_WEIGHT_CPU_PERMUTE=0; export MODEL_REFERENCES_ROOT=/Model-References; export ENABLE_CONSOLE=false; export LOG_LEVEL_ALL=4;  cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed; /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMzcuMTc1IjogWzAsIDEsIDIsIDMsIDQsIDUsIDYsIDddLCAiMTAwLjgzLjM3LjE4OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --node_rank=%n --master_addr=100.83.37.175 --master_port=29500 --no_python --no_local_rank /usr/bin/bash -c '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:34:09/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:34:09/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:34:09/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/llama13b_multiling_800M/13-05-2024-09:34:09/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:34:09/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'
+100.83.37.175: Warning: Permanently added '[100.83.37.175]:3122' (ED25519) to the list of known hosts.
+100.83.37.188: Warning: Permanently added '[100.83.37.188]:3122' (ED25519) to the list of known hosts.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:34:14,112] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:34:14,229] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:34:15,453] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.188: [2024-05-13 09:34:15,454] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=1
+100.83.37.188: [2024-05-13 09:34:15,454] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.188: [2024-05-13 09:34:15,454] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.188: [2024-05-13 09:34:15,454] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175: [2024-05-13 09:34:15,503] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.175: [2024-05-13 09:34:15,503] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=0
+100.83.37.175: [2024-05-13 09:34:15,503] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.175: [2024-05-13 09:34:15,503] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.175: [2024-05-13 09:34:15,503] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.175: [2024-05-13 09:34:17,241] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:34:17,263] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:34:17,267] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:34:17,266] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.188: [2024-05-13 09:34:17,266] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:34:17,267] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:34:17,314] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:34:17,373] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.175: [2024-05-13 09:34:17,383] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:34:17,386] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:34:17,387] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:34:17,439] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.188: [2024-05-13 09:34:17,464] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:34:17,465] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:34:17,467] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: [2024-05-13 09:34:17,530] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.188: ----------------------------------------------------------------------------------------------------
+100.83.37.188: 
+100.83.37.188: DeepSpeed C++/CUDA extension op report
+100.83.37.188: DeepSpeed C++/CUDA extension op report--------------------------------------------------
+100.83.37.188: 
+100.83.37.188: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.188:       runtime if needed. Op compatibility means that your system
+100.83.37.188:       meet the required dependencies to JIT install the op.--------------------------------------------------
+100.83.37.188: --------------------------------------------------
+100.83.37.188: 
+100.83.37.188: JIT compiled ops requires ninja
+100.83.37.188: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.188:       runtime if needed. Op compatibility means that your system
+100.83.37.188:       meet the required dependencies to JIT install the op.
+100.83.37.188: --------------------------------------------------
+100.83.37.188: JIT compiled ops requires ninja
+100.83.37.188: ninja ninja..................  [OKAY].................. 
+100.83.37.188: [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: --------------------------------------------------
+100.83.37.188: op name op name................  ................installed  installed..  ..compatible 
+100.83.37.188: compatible--------------------------------------------------
+100.83.37.188: 
+100.83.37.188: --------------------------------------------------
+100.83.37.188: cpu_adam ...............cpu_adam  [NO]...............  .......[NO]  [OKAY].......
+100.83.37.188:  [OKAY]
+100.83.37.188: fused_adam fused_adam.............  .............[NO]  [NO].......  [OKAY].......
+100.83.37.188:  [OKAY]
+100.83.37.188: deepspeed_not_implemented  deepspeed_not_implemented[NO]  .......  [OKAY][NO]
+100.83.37.188:  ....... transformer_inference[OKAY] 
+100.83.37.188: .. [NO] transformer_inference.......  ..[OKAY] 
+100.83.37.188: [NO]-------------------------------------------------- 
+100.83.37.188: ....... [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed general environment info:
+100.83.37.188: torch install path ...............DeepSpeed general environment info: 
+100.83.37.188: torch install path['/usr/local/lib/python3.10/dist-packages/torch'] 
+100.83.37.188: ............... torch version .................... 2.1.1a0+gitb51c9f6['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.188: deepspeed install path 
+100.83.37.188: ........... torch version['/usr/local/lib/python3.10/dist-packages/deepspeed'] 
+100.83.37.188: .................... deepspeed info 2.1.1a0+gitb51c9f6...................
+100.83.37.188:  0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0deepspeed install path
+100.83.37.188:  deepspeed wheel compiled w............  ...... ['/usr/local/lib/python3.10/dist-packages/deepspeed']torch 2.1 
+100.83.37.188: 
+100.83.37.188: deepspeed infoshared memory (/dev/shm) size  .......................  0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0503.75 GB
+100.83.37.188: 
+100.83.37.188: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.188: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed C++/CUDA extension op report
+100.83.37.188: --------------------------------------------------
+100.83.37.188: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.188:       runtime if needed. Op compatibility means that your system
+100.83.37.188:       meet the required dependencies to JIT install the op.
+100.83.37.188: --------------------------------------------------
+100.83.37.188: JIT compiled ops requires ninja
+100.83.37.188: ninja .................. [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: op name ................ installed .. compatible
+100.83.37.188: --------------------------------------------------
+100.83.37.188: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.188: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.188: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.188: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed general environment info:
+100.83.37.188: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.188: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.188: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.188: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.188: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.188: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.188: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.188: To add an exception for this directory, call:
+100.83.37.188: 
+100.83.37.188: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.188: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.188: To add an exception for this directory, call:
+100.83.37.188: 
+100.83.37.188: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.188: **** Git info for Megatron: git_hash=unknown git_branch=unknown ******** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.188: 
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.188:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.188:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.188: TypeError: TypeErrorpretrain() missing 1 required positional argument: 'forward_step_func': 
+100.83.37.188: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.188: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.188: To add an exception for this directory, call:
+100.83.37.188: 
+100.83.37.188: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.188: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.188:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.188: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed C++/CUDA extension op report
+100.83.37.188: --------------------------------------------------
+100.83.37.188: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.188:       runtime if needed. Op compatibility means that your system
+100.83.37.188:       meet the required dependencies to JIT install the op.
+100.83.37.188: --------------------------------------------------
+100.83.37.188: JIT compiled ops requires ninja
+100.83.37.188: ninja .................. [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: op name ................ installed .. compatible
+100.83.37.188: --------------------------------------------------
+100.83.37.188: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.188: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.188: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.188: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed general environment info:
+100.83.37.188: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.188: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.188: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.188: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.188: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.188: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.188: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.188: To add an exception for this directory, call:
+100.83.37.188: 
+100.83.37.188: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.188: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.188:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.188: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed C++/CUDA extension op report
+100.83.37.188: --------------------------------------------------
+100.83.37.188: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.188:       runtime if needed. Op compatibility means that your system
+100.83.37.188:       meet the required dependencies to JIT install the op.
+100.83.37.188: --------------------------------------------------
+100.83.37.188: JIT compiled ops requires ninja
+100.83.37.188: ninja .................. [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: op name ................ installed .. compatible
+100.83.37.188: --------------------------------------------------
+100.83.37.188: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.188: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.188: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.188: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed general environment info:
+100.83.37.188: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.188: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.188: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.188: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.188: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.188: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed C++/CUDA extension op report
+100.83.37.188: --------------------------------------------------
+100.83.37.188: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.188:       runtime if needed. Op compatibility means that your system
+100.83.37.188:       meet the required dependencies to JIT install the op.
+100.83.37.188: --------------------------------------------------
+100.83.37.188: JIT compiled ops requires ninja
+100.83.37.188: ninja .................. [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: op name ................ installed .. compatible
+100.83.37.188: --------------------------------------------------
+100.83.37.188: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.188: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.188: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.188: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed general environment info:
+100.83.37.188: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.188: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.188: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.188: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.188: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.188: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.188: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.188: To add an exception for this directory, call:
+100.83.37.188: 
+100.83.37.188: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.188: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.188:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.188: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.188: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.188: To add an exception for this directory, call:
+100.83.37.188: 
+100.83.37.188: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.188: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.188:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.188: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed C++/CUDA extension op report
+100.83.37.175: --------------------------------------------------
+100.83.37.175: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.175:       runtime if needed. Op compatibility means that your system
+100.83.37.175:       meet the required dependencies to JIT install the op.
+100.83.37.175: --------------------------------------------------
+100.83.37.175: JIT compiled ops requires ninja
+100.83.37.175: ninja .................. [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: op name ................ installed .. compatible
+100.83.37.175: --------------------------------------------------
+100.83.37.175: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.175: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.175: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.175: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed general environment info:
+100.83.37.175: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.175: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.175: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.175: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.175: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.175: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.175: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.175: To add an exception for this directory, call:
+100.83.37.175: 
+100.83.37.175: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.175: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.175:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.175: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed C++/CUDA extension op report
+100.83.37.175: --------------------------------------------------
+100.83.37.175: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.175:       runtime if needed. Op compatibility means that your system
+100.83.37.175:       meet the required dependencies to JIT install the op.
+100.83.37.175: --------------------------------------------------
+100.83.37.175: JIT compiled ops requires ninja
+100.83.37.175: ninja .................. [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: op name ................ installed .. compatible
+100.83.37.175: --------------------------------------------------
+100.83.37.175: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.175: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.175: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.175: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed general environment info:
+100.83.37.175: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.175: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.175: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.175: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.175: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.175: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.175: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.175: To add an exception for this directory, call:
+100.83.37.175: 
+100.83.37.175: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.175: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.175:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.175: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed C++/CUDA extension op report
+100.83.37.188: --------------------------------------------------
+100.83.37.188: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.188:       runtime if needed. Op compatibility means that your system
+100.83.37.188:       meet the required dependencies to JIT install the op.
+100.83.37.188: --------------------------------------------------
+100.83.37.188: JIT compiled ops requires ninja
+100.83.37.188: ninja .................. [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: op name ................ installed .. compatible
+100.83.37.188: --------------------------------------------------
+100.83.37.188: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.188: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.188: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.188: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed general environment info:
+100.83.37.188: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.188: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.188: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.188: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.188: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.188: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed C++/CUDA extension op report
+100.83.37.188: --------------------------------------------------
+100.83.37.188: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.188:       runtime if needed. Op compatibility means that your system
+100.83.37.188:       meet the required dependencies to JIT install the op.
+100.83.37.188: --------------------------------------------------
+100.83.37.188: JIT compiled ops requires ninja
+100.83.37.188: ninja .................. [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: op name ................ installed .. compatible
+100.83.37.188: --------------------------------------------------
+100.83.37.188: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.188: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.188: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.188: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.188: --------------------------------------------------
+100.83.37.188: DeepSpeed general environment info:
+100.83.37.188: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.188: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.188: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.188: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.188: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.188: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.188: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.188: To add an exception for this directory, call:
+100.83.37.188: 
+100.83.37.188: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.188: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.188:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.188: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.188: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.188: To add an exception for this directory, call:
+100.83.37.188: 
+100.83.37.188: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.188: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.188: Traceback (most recent call last):
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.188:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.188: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed C++/CUDA extension op report
+100.83.37.175: --------------------------------------------------
+100.83.37.175: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.175:       runtime if needed. Op compatibility means that your system
+100.83.37.175:       meet the required dependencies to JIT install the op.
+100.83.37.175: --------------------------------------------------
+100.83.37.175: JIT compiled ops requires ninja
+100.83.37.175: ninja .................. [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: op name ................ installed .. compatible
+100.83.37.175: --------------------------------------------------
+100.83.37.175: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.175: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.175: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.175: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed general environment info:
+100.83.37.175: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.175: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.175: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.175: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.175: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.175: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.175: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.175: To add an exception for this directory, call:
+100.83.37.175: 
+100.83.37.175: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.175: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.175:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.175: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed C++/CUDA extension op report
+100.83.37.175: --------------------------------------------------
+100.83.37.175: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.175:       runtime if needed. Op compatibility means that your system
+100.83.37.175:       meet the required dependencies to JIT install the op.
+100.83.37.175: --------------------------------------------------
+100.83.37.175: JIT compiled ops requires ninja
+100.83.37.175: ninja .................. [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: op name ................ installed .. compatible
+100.83.37.175: --------------------------------------------------
+100.83.37.175: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.175: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.175: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.175: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed general environment info:
+100.83.37.175: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.175: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.175: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.175: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.175: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.175: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.175: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.175: To add an exception for this directory, call:
+100.83.37.175: 
+100.83.37.175: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.175: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.175:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.175: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed C++/CUDA extension op report
+100.83.37.175: --------------------------------------------------
+100.83.37.175: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.175:       runtime if needed. Op compatibility means that your system
+100.83.37.175:       meet the required dependencies to JIT install the op.
+100.83.37.175: --------------------------------------------------
+100.83.37.175: JIT compiled ops requires ninja
+100.83.37.175: ninja .................. [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: op name ................ installed .. compatible
+100.83.37.175: --------------------------------------------------
+100.83.37.175: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.175: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.175: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.175: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed general environment info:
+100.83.37.175: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.175: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.175: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.175: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.175: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.175: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.175: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.175: To add an exception for this directory, call:
+100.83.37.175: 
+100.83.37.175: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.175: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.175:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.175: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed C++/CUDA extension op report
+100.83.37.175: --------------------------------------------------
+100.83.37.175: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.175:       runtime if needed. Op compatibility means that your system
+100.83.37.175:       meet the required dependencies to JIT install the op.
+100.83.37.175: --------------------------------------------------
+100.83.37.175: JIT compiled ops requires ninja
+100.83.37.175: ninja .................. [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: op name ................ installed .. compatible
+100.83.37.175: --------------------------------------------------
+100.83.37.175: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.175: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.175: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.175: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed general environment info:
+100.83.37.175: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.175: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.175: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.175: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.175: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.175: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.175: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.175: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.175: To add an exception for this directory, call:
+100.83.37.175: 
+100.83.37.175: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.175:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.175: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed C++/CUDA extension op report
+100.83.37.175: --------------------------------------------------
+100.83.37.175: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.175:       runtime if needed. Op compatibility means that your system
+100.83.37.175:       meet the required dependencies to JIT install the op.
+100.83.37.175: --------------------------------------------------
+100.83.37.175: JIT compiled ops requires ninja
+100.83.37.175: ninja .................. [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: op name ................ installed .. compatible
+100.83.37.175: --------------------------------------------------
+100.83.37.175: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.175: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.175: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.175: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed general environment info:
+100.83.37.175: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.175: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.175: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.175: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.175: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.175: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.175: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.175: To add an exception for this directory, call:
+100.83.37.175: 
+100.83.37.175: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.175: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.175:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.175: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed C++/CUDA extension op report
+100.83.37.175: --------------------------------------------------
+100.83.37.175: NOTE: Ops not installed will be just-in-time (JIT) compiled at
+100.83.37.175:       runtime if needed. Op compatibility means that your system
+100.83.37.175:       meet the required dependencies to JIT install the op.
+100.83.37.175: --------------------------------------------------
+100.83.37.175: JIT compiled ops requires ninja
+100.83.37.175: ninja .................. [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: op name ................ installed .. compatible
+100.83.37.175: --------------------------------------------------
+100.83.37.175: cpu_adam ............... [NO] ....... [OKAY]
+100.83.37.175: fused_adam ............. [NO] ....... [OKAY]
+100.83.37.175: deepspeed_not_implemented  [NO] ....... [OKAY]
+100.83.37.175: transformer_inference .. [NO] ....... [OKAY]
+100.83.37.175: --------------------------------------------------
+100.83.37.175: DeepSpeed general environment info:
+100.83.37.175: torch install path ............... ['/usr/local/lib/python3.10/dist-packages/torch']
+100.83.37.175: torch version .................... 2.1.1a0+gitb51c9f6
+100.83.37.175: deepspeed install path ........... ['/usr/local/lib/python3.10/dist-packages/deepspeed']
+100.83.37.175: deepspeed info ................... 0.12.4+hpu.synapse.v1.14.0, fad45b2, 1.14.0
+100.83.37.175: deepspeed wheel compiled w. ...... torch 2.1 
+100.83.37.175: shared memory (/dev/shm) size .... 503.75 GB
+100.83.37.175: fatal: detected dubious ownership in repository at '/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed'
+100.83.37.175: To add an exception for this directory, call:
+100.83.37.175: 
+100.83.37.175: 	git config --global --add safe.directory /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed
+100.83.37.175: **** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+100.83.37.175: Traceback (most recent call last):
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+100.83.37.175:     pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+100.83.37.175: TypeError: pretrain() missing 1 required positional argument: 'forward_step_func'
+100.83.37.188: [2024-05-13 09:34:20,462] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 124734
+100.83.37.188: [2024-05-13 09:34:20,463] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 124735
+100.83.37.188: [2024-05-13 09:34:20,464] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 124736
+100.83.37.188: [2024-05-13 09:34:20,464] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 124737
+100.83.37.188: [2024-05-13 09:34:20,464] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 124738
+100.83.37.188: [2024-05-13 09:34:20,464] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 124739
+100.83.37.188: [2024-05-13 09:34:20,465] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 124740
+100.83.37.188: [2024-05-13 09:34:20,465] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 124741
+100.83.37.188: [2024-05-13 09:34:20,465] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:34:09/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:34:09/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:34:09/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/llama13b_multiling_800M/13-05-2024-09:34:09/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:34:09/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+100.83.37.175: [2024-05-13 09:34:20,512] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 29973
+100.83.37.175: [2024-05-13 09:34:20,514] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 29974
+100.83.37.175: [2024-05-13 09:34:20,514] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 29975
+100.83.37.175: [2024-05-13 09:34:20,515] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 29976
+100.83.37.175: [2024-05-13 09:34:20,515] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 29979
+100.83.37.175: [2024-05-13 09:34:20,516] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 29982
+100.83.37.175: [2024-05-13 09:34:20,516] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 29987
+100.83.37.175: [2024-05-13 09:34:20,516] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 29988
+100.83.37.175: [2024-05-13 09:34:20,517] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:34:09/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:34:09/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:34:09/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/llama13b_multiling_800M/13-05-2024-09:34:09/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:34:09/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.175: ssh exited with exit code 1
+pdsh@vizzhy-150-3: 100.83.37.188: ssh exited with exit code 1

llama13b_multiling_800M/13-05-2024-09:34:09/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-09:58:53/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:58:53/log.txt

@@ -0,0 +1,128 @@
+/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(
+[2024-05-13 09:58:54,809] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-05-13 09:58:56,129] [INFO] [runner.py:574:main] deepspeed_env file = /root/.deepspeed_env
+[2024-05-13 09:58:56,129] [INFO] [multinode_runner.py:72:get_cmd] Running on the following workers: 100.83.37.175,100.83.37.188
+[2024-05-13 09:58:56,129] [INFO] [runner.py:585:main] cmd = pdsh -S -f 1024 -w 100.83.37.175,100.83.37.188 export PYTHONPATH=/Model-References/PyTorch/common:/usr/lib/habanalabs/:$PYTHONPATH; export PYTHON=/usr/bin/python3; export PT_HPU_LAZY_ACC_PAR_MODE=0; export PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES=0; export PT_HPU_ENABLE_WEIGHT_CPU_PERMUTE=0; export MODEL_REFERENCES_ROOT=/Model-References; export ENABLE_CONSOLE=false; export LOG_LEVEL_ALL=4;  cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed; /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMzcuMTc1IjogWzAsIDEsIDIsIDMsIDQsIDUsIDYsIDddLCAiMTAwLjgzLjM3LjE4OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --node_rank=%n --master_addr=100.83.37.175 --master_port=29500 --no_python --no_local_rank /usr/bin/bash -c '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:58:53/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:58:53/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:58:53/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/llama13b_multiling_800M/13-05-2024-09:58:53/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:58:53/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'
+100.83.37.175: Warning: Permanently added '[100.83.37.175]:3122' (ED25519) to the list of known hosts.
+100.83.37.188: Warning: Permanently added '[100.83.37.188]:3122' (ED25519) to the list of known hosts.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 09:58:57,783] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 09:58:57,862] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 09:58:58,998] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.188: [2024-05-13 09:58:58,998] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=1
+100.83.37.188: [2024-05-13 09:58:58,998] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.188: [2024-05-13 09:58:58,998] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.188: [2024-05-13 09:58:58,998] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     )
+100.83.37.188: IndentationError: unexpected indent
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     )
+100.83.37.188: IndentationError: unexpected indent
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     )
+100.83.37.188: IndentationError: unexpected indent
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     )
+100.83.37.188: IndentationError: unexpected indent
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     )
+100.83.37.188: IndentationError: unexpected indent
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     )
+100.83.37.188: IndentationError: unexpected indent
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     )
+100.83.37.188: IndentationError: unexpected indent
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     )
+100.83.37.188: IndentationError: unexpected indent
+100.83.37.175: [2024-05-13 09:58:59,320] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.175: [2024-05-13 09:58:59,320] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=0
+100.83.37.175: [2024-05-13 09:58:59,320] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.175: [2024-05-13 09:58:59,320] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.175: [2024-05-13 09:58:59,320] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:     )
+100.83.37.175: IndentationError: unexpected indent
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:     )
+100.83.37.175: IndentationError: unexpected indent
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:     )
+100.83.37.175: IndentationError: unexpected indent
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:     )
+100.83.37.175: IndentationError: unexpected indent
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:     )
+100.83.37.175:     )
+100.83.37.175: IndentationError: IndentationErrorunexpected indent: 
+100.83.37.175: unexpected indent
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:     )
+100.83.37.175: IndentationError: unexpected indent
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:     )
+100.83.37.175: IndentationError: unexpected indent
+100.83.37.188: [2024-05-13 09:59:00,002] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 126123
+100.83.37.188: [2024-05-13 09:59:00,003] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 126124
+100.83.37.188: [2024-05-13 09:59:00,003] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 126125
+100.83.37.188: [2024-05-13 09:59:00,004] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 126126
+100.83.37.188: [2024-05-13 09:59:00,004] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 126127
+100.83.37.188: [2024-05-13 09:59:00,004] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 126128
+100.83.37.188: [2024-05-13 09:59:00,004] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 126129
+100.83.37.188: [2024-05-13 09:59:00,004] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 126130
+100.83.37.188: [2024-05-13 09:59:00,005] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:58:53/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:58:53/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:58:53/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/llama13b_multiling_800M/13-05-2024-09:58:53/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:58:53/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.188: ssh exited with exit code 1
+100.83.37.175: [2024-05-13 09:59:00,324] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 31578
+100.83.37.175: [2024-05-13 09:59:00,326] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 31579
+100.83.37.175: [2024-05-13 09:59:00,326] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 31580
+100.83.37.175: [2024-05-13 09:59:00,327] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 31581
+100.83.37.175: [2024-05-13 09:59:00,327] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 31585
+100.83.37.175: [2024-05-13 09:59:00,328] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 31590
+100.83.37.175: [2024-05-13 09:59:00,328] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 31592
+100.83.37.175: [2024-05-13 09:59:00,328] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 31599
+100.83.37.175: [2024-05-13 09:59:00,329] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-09:58:53/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-09:58:53/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-09:58:53/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/llama13b_multiling_800M/13-05-2024-09:58:53/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-09:58:53/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.175: ssh exited with exit code 1

llama13b_multiling_800M/13-05-2024-09:58:53/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-09:59:29/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-09:59:29/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-11:50:01/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-11:50:01/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-11:52:31/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-11:52:31/log.txt

@@ -0,0 +1,144 @@
+/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(
+[2024-05-13 11:52:33,447] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-05-13 11:52:34,769] [INFO] [runner.py:574:main] deepspeed_env file = /root/.deepspeed_env
+[2024-05-13 11:52:34,769] [INFO] [multinode_runner.py:72:get_cmd] Running on the following workers: 100.83.37.175,100.83.37.188
+[2024-05-13 11:52:34,769] [INFO] [runner.py:585:main] cmd = pdsh -S -f 1024 -w 100.83.37.175,100.83.37.188 export PYTHONPATH=/Model-References/PyTorch/common:/usr/lib/habanalabs/:$PYTHONPATH; export PYTHON=/usr/bin/python3; export PT_HPU_LAZY_ACC_PAR_MODE=0; export PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES=0; export PT_HPU_ENABLE_WEIGHT_CPU_PERMUTE=0; export MODEL_REFERENCES_ROOT=/Model-References; export ENABLE_CONSOLE=false; export LOG_LEVEL_ALL=4;  cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed; /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMzcuMTc1IjogWzAsIDEsIDIsIDMsIDQsIDUsIDYsIDddLCAiMTAwLjgzLjM3LjE4OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --node_rank=%n --master_addr=100.83.37.175 --master_port=29500 --no_python --no_local_rank /usr/bin/bash -c '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-11:52:31/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-11:52:31/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-11:52:31/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/llama13b_multiling_800M/13-05-2024-11:52:31/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-11:52:31/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'
+100.83.37.175: Warning: Permanently added '[100.83.37.175]:3122' (ED25519) to the list of known hosts.
+100.83.37.188: Warning: Permanently added '[100.83.37.188]:3122' (ED25519) to the list of known hosts.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.175: /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.
+100.83.37.175:   warnings.warn(
+100.83.37.175: [2024-05-13 11:52:36,438] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: /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.
+100.83.37.188:   warnings.warn(
+100.83.37.188: [2024-05-13 11:52:36,472] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+100.83.37.188: [2024-05-13 11:52:37,597] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.188: [2024-05-13 11:52:37,597] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=1
+100.83.37.188: [2024-05-13 11:52:37,597] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.188: [2024-05-13 11:52:37,597] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.188: [2024-05-13 11:52:37,597] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:    ...done.
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     data_post_process=data_post_process)
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:                File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188: data_post_process=data_post_process)
+100.83.37.188:  data_post_process=data_post_process)
+100.83.37.188:                data_post_process=data_post_process)
+100.83.37.188:                                                                                                                                        ^  ^
+100.83.37.188: ^
+100.83.37.188:  
+100.83.37.188:  SyntaxError^SyntaxErrorSyntaxError: 
+100.83.37.188: : : positional argument follows keyword argumentpositional argument follows keyword argumentpositional argument follows keyword argumentSyntaxError
+100.83.37.188: 
+100.83.37.188: 
+100.83.37.188: : positional argument follows keyword argument
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     data_post_process=data_post_process)
+100.83.37.188:                    File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:          data_post_process=data_post_process)
+100.83.37.188:                                     ^ 
+100.83.37.188:     SyntaxError  :  positional argument follows keyword argument 
+100.83.37.188:            ^
+100.83.37.188: SyntaxError: positional argument follows keyword argument
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     data_post_process=data_post_process)
+100.83.37.188:                                        ^
+100.83.37.188: SyntaxError: positional argument follows keyword argument
+100.83.37.188:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.188:     data_post_process=data_post_process)
+100.83.37.188:                                        ^
+100.83.37.188: SyntaxError: positional argument follows keyword argument
+100.83.37.175: [2024-05-13 11:52:37,832] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [0, 1, 2, 3, 4, 5, 6, 7]}
+100.83.37.175: [2024-05-13 11:52:37,832] [INFO] [launch.py:152:main] nnodes=2, num_local_procs=8, node_rank=0
+100.83.37.175: [2024-05-13 11:52:37,832] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.37.175': [0, 1, 2, 3, 4, 5, 6, 7], '100.83.37.188': [8, 9, 10, 11, 12, 13, 14, 15]})
+100.83.37.175: [2024-05-13 11:52:37,832] [INFO] [launch.py:164:main] dist_world_size=16
+100.83.37.175: [2024-05-13 11:52:37,832] [INFO] [launch.py:166:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:    ...done.
+100.83.37.175:  * Starting OpenBSD Secure Shell server sshd
+100.83.37.175:    ...done.
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:             data_post_process=data_post_process)
+100.83.37.175: data_post_process=data_post_process)
+100.83.37.175:     data_post_process=data_post_process)
+100.83.37.175:                                                                                                             ^  
+100.83.37.175:    ^^SyntaxError
+100.83.37.175: 
+100.83.37.175: : positional argument follows keyword argument
+100.83.37.175: SyntaxErrorSyntaxError: : positional argument follows keyword argumentpositional argument follows keyword argument
+100.83.37.175: 
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:     data_post_process=data_post_process)
+100.83.37.175:                File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:   File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:    File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:              data_post_process=data_post_process)
+100.83.37.175:  data_post_process=data_post_process)
+100.83.37.175:      data_post_process=data_post_process)
+100.83.37.175:                                                  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 119
+100.83.37.175:            data_post_process=data_post_process)
+100.83.37.175:                                                         ^    
+100.83.37.175:  SyntaxError    :     positional argument follows keyword argument     
+100.83.37.175:                         ^ 
+100.83.37.175:     SyntaxError  :     positional argument follows keyword argument^ 
+100.83.37.175: ^
+100.83.37.175:  SyntaxError
+100.83.37.175:  :  SyntaxErrorpositional argument follows keyword argument : 
+100.83.37.175:  positional argument follows keyword argument 
+100.83.37.175:     ^
+100.83.37.175: SyntaxError: positional argument follows keyword argument
+100.83.37.188: [2024-05-13 11:52:38,601] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 129388
+100.83.37.188: [2024-05-13 11:52:38,602] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 129389
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+100.83.37.188: [2024-05-13 11:52:38,603] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 129391
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+100.83.37.188: [2024-05-13 11:52:38,603] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 129394
+100.83.37.188: [2024-05-13 11:52:38,604] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 129395
+100.83.37.188: [2024-05-13 11:52:38,604] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-11:52:31/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-11:52:31/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-11:52:31/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/llama13b_multiling_800M/13-05-2024-11:52:31/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-11:52:31/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+100.83.37.175: [2024-05-13 11:52:38,836] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 35482
+100.83.37.175: [2024-05-13 11:52:38,838] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 35483
+100.83.37.175: [2024-05-13 11:52:38,838] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 35484
+100.83.37.175: [2024-05-13 11:52:38,839] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 35485
+100.83.37.175: [2024-05-13 11:52:38,839] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 35488
+100.83.37.175: [2024-05-13 11:52:38,840] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 35489
+100.83.37.175: [2024-05-13 11:52:38,840] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 35492
+100.83.37.175: [2024-05-13 11:52:38,840] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 35496
+100.83.37.175: [2024-05-13 11:52:38,841] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 24     --hidden-size 2048     --ffn-hidden-size 4096     --num-attention-heads 32     --seq-length 2048     --micro-batch-size 1     --global-batch-size 256     --train-iters 10000     --log-interval 10     --eval-iters 10     --eval-interval 500     --data-path /data/hineng/tokenizer//_raw_content_document     --vocab-file /data/hineng/tokenizer//gpt2-vocab.json     --merge-file /data/hineng/tokenizer//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/llama13b_multiling_800M/13-05-2024-11:52:31/tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_multiling_800M/13-05-2024-11:52:31/checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_multiling_800M/13-05-2024-11:52:31/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/llama13b_multiling_800M/13-05-2024-11:52:31/checkpoints_zero_stage_2 --hf-save /data/output/llama13b_multiling_800M/13-05-2024-11:52:31/hf_ckpt --save-interval 500 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1
+pdsh@vizzhy-150-3: 100.83.37.188: ssh exited with exit code 1
+pdsh@vizzhy-150-3: 100.83.37.175: ssh exited with exit code 1

llama13b_multiling_800M/13-05-2024-11:52:31/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_multiling_800M/13-05-2024-11:55:44/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_multiling_800M/13-05-2024-11:55:44/mds_to_hf_llama_custom.json

@@ -0,0 +1,40 @@
+{
+    "MODEL": {
+        "num_hidden_layers": 24,
+        "hidden_size": 2048,
+        "num_attention_heads": 32,
+        "intermediate_size": 4096,
+	"vocab_size":VOCAB_SIZE
+    },
+    "LAYER_MAPPINGS" : {
+        "word_embeddings": 1,
+        "transformer": [3, 26],
+        "final_layernorm": 28,
+        "final_word_embeddings": 29
+    },
+    "FULL_NAME_MAPPINGS": {
+    },
+    "PARTIAL_NAME_MAPPINGS": {
+        "final_word_embeddings": {
+            "vocab_parallel_projection": "lm_head"
+        },
+        "final_layernorm": {
+            "final_rmsnorm": "model.norm"
+        },
+        "word_embeddings": {
+            "word_embeddings": "model.embed_tokens"
+        },
+        "transformer": {
+            "dense_h_to_4h": "mlp.gate_proj",
+            "dense_4h_to_h": "mlp.down_proj",
+            "dense_h_to_4h_swiglu": "mlp.up_proj",
+            "post_attention_layernorm": "post_attention_layernorm",
+            "input_layernorm": "input_layernorm",
+            "dense": "self_attn.o_proj",
+            "query_key_value": {"query": "self_attn.q_proj", "key": "self_attn.k_proj", "value": "self_attn.v_proj"}
+        }
+    },
+    "SPECIAL": {
+        "query_key_value": "attention_qkv"
+    }
+}

llama13b_x/ds_config.json

@@ -0,0 +1,19 @@
+{
+  "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
+  }
+}

llama13b_x/log.txt

@@ -0,0 +1,857 @@
+/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(
+[2024-04-17 13:35:41,775] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-04-17 13:36:22,312] [INFO] [runner.py:585:main] cmd = /usr/bin/python3 -u -m deepspeed.launcher.launch --world_info=eyIxMDAuODMuMTM0LjE1OCI6IFswLCAxLCAyLCAzLCA0LCA1LCA2LCA3XX0= --master_addr=100.83.134.158 --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 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 16     --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/llama13b_x//tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_x//checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_x//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/llama13b_x//checkpoints_zero_stage_2 --hf-save /data/output/llama13b_x//hf_ckpt --save-interval 100 --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(
+[2024-04-17 13:36:23,803] [INFO] [real_accelerator.py:178:get_accelerator] Setting ds_accelerator to hpu (auto detect)
+[2024-04-17 13:36:24,923] [INFO] [launch.py:146:main] WORLD INFO DICT: {'100.83.134.158': [0, 1, 2, 3, 4, 5, 6, 7]}
+[2024-04-17 13:36:24,923] [INFO] [launch.py:152:main] nnodes=1, num_local_procs=8, node_rank=0
+[2024-04-17 13:36:24,923] [INFO] [launch.py:163:main] global_rank_mapping=defaultdict(<class 'list'>, {'100.83.134.158': [0, 1, 2, 3, 4, 5, 6, 7]})
+[2024-04-17 13:36:24,923] [INFO] [launch.py:164:main] dist_world_size=8
+[2024-04-17 13:36:24,923] [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(
+[2024-04-17 13:36:26,736] [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(
+[2024-04-17 13:36:26,736] [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(
+[2024-04-17 13:36:26,798] [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(
+[2024-04-17 13:36:26,801] [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(
+[2024-04-17 13:36:26,864] [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(
+[2024-04-17 13:36:26,902] [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(
+[2024-04-17 13:36:26,912] [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(
+[2024-04-17 13:36:26,977] [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
+--------------------------------------------------
+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 ****
+--------------------------------------------------
+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: 8, tensor-model-parallel size: 1, pipeline-model-parallel size: 1 
+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 .............................. 8
+  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/llama13b_x//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
+  hf_save ......................................... /data/output/llama13b_x//hf_ckpt
+  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/llama13b_x//checkpoints_zero_stage_2
+  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 ...................................... 16
+  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 .................... 1
+  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/llama13b_x//checkpoints_zero_stage_2
+  save_interval ................................... 100
+  scatter_gather_tensors_in_pipeline .............. True
+  scattered_embeddings ............................ False
+  seed ............................................ 1234
+  seq_length ...................................... 2048
+  sequence_parallel ............................... False
+  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 ...................... 1
+  tensorboard_dir ................................. /data/output/llama13b_x//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 32
+setting number of micro-batches to constant 32
+> building GPT2BPETokenizer tokenizer ...
+_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
+_initialize_distributed: Initializing with below params:
+args.local_rank: 4
+args.world_size: 8
+args.rank: 4
+args.distributed_backend: hccl
+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
+ > padded vocab (size: 50257) with 47 dummy tokens (new size: 50304)
+_initialize_distributed: Initializing with below params:
+args.local_rank: 0
+args.world_size: 8
+args.rank: 0
+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
+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
+[2024-04-17 13:36:29,411] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
+[2024-04-17 13:36:29,411] [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
+[2024-04-17 13:36:29,416] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
+[2024-04-17 13:36:29,416] [INFO] [comm.py:637:init_distributed] cdb=None
+_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: 6
+args.world_size: 8
+args.rank: 6
+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
+--------------------------------------------------
+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
+> initializing torch distributed ...
+[2024-04-17 13:36:29,471] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
+[2024-04-17 13:36:29,471] [INFO] [comm.py:637:init_distributed] cdb=None
+[2024-04-17 13:36:29,471] [INFO] [comm.py:668:init_distributed] Initializing TorchBackend in DeepSpeed with backend hccl
+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
+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
+[2024-04-17 13:36:29,495] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
+[2024-04-17 13:36:29,496] [INFO] [comm.py:637:init_distributed] cdb=None
+**** Git info for Megatron: git_hash=unknown git_branch=unknown ****
+> 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
+[2024-04-17 13:36:29,532] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
+[2024-04-17 13:36:29,532] [INFO] [comm.py:637:init_distributed] cdb=None
+_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: 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
+[2024-04-17 13:36:29,568] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
+[2024-04-17 13:36:29,568] [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
+[2024-04-17 13:36:29,609] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
+[2024-04-17 13:36:29,610] [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
+[2024-04-17 13:36:29,627] [WARNING] [comm.py:163:init_deepspeed_backend] HCCL backend in DeepSpeed not yet implemented
+[2024-04-17 13:36:29,627] [INFO] [comm.py:637:init_distributed] cdb=None
+[E socket.cpp:922] [c10d] The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+Traceback (most recent call last):
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+    pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/training.py", line 162, in pretrain
+    initialize_megatron(extra_args_provider=extra_args_provider,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 95, in initialize_megatron
+    finish_mpu_init()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 77, in finish_mpu_init
+    _initialize_distributed()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 276, in _initialize_distributed
+    deepspeed.init_distributed(dist_backend=args.distributed_backend)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/comm.py", line 670, in init_distributed
+    cdb = TorchBackend(dist_backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 120, in __init__
+[E socket.cpp:922] [c10d] The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+    self.init_process_group(backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 148, in init_process_group
+    torch.distributed.init_process_group(backend, timeout=timeout, init_method=init_method)
+  File "/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/torch_overwrites.py", line 259, in wrap_init_process_group
+    return init_process_group_orig(
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/c10d_logger.py", line 74, in wrapper
+    func_return = func(*args, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 1141, in init_process_group
+Traceback (most recent call last):
+    store, rank, world_size = next(rendezvous_iterator)
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 241, in _env_rendezvous_handler
+    store = _create_c10d_store(master_addr, master_port, rank, world_size, timeout)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 172, in _create_c10d_store
+    return TCPStore(
+TimeoutError: The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+    pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/training.py", line 162, in pretrain
+    initialize_megatron(extra_args_provider=extra_args_provider,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 95, in initialize_megatron
+    finish_mpu_init()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 77, in finish_mpu_init
+    _initialize_distributed()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 276, in _initialize_distributed
+    deepspeed.init_distributed(dist_backend=args.distributed_backend)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/comm.py", line 670, in init_distributed
+    cdb = TorchBackend(dist_backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 120, in __init__
+    self.init_process_group(backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 148, in init_process_group
+    torch.distributed.init_process_group(backend, timeout=timeout, init_method=init_method)
+  File "/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/torch_overwrites.py", line 259, in wrap_init_process_group
+    return init_process_group_orig(
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/c10d_logger.py", line 74, in wrapper
+    func_return = func(*args, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 1141, in init_process_group
+    store, rank, world_size = next(rendezvous_iterator)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 241, in _env_rendezvous_handler
+    store = _create_c10d_store(master_addr, master_port, rank, world_size, timeout)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 172, in _create_c10d_store
+    return TCPStore(
+TimeoutError: The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+[E socket.cpp:922] [c10d] The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+Traceback (most recent call last):
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+    pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/training.py", line 162, in pretrain
+    initialize_megatron(extra_args_provider=extra_args_provider,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 95, in initialize_megatron
+    finish_mpu_init()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 77, in finish_mpu_init
+    _initialize_distributed()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 276, in _initialize_distributed
+    deepspeed.init_distributed(dist_backend=args.distributed_backend)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/comm.py", line 670, in init_distributed
+    cdb = TorchBackend(dist_backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 120, in __init__
+    self.init_process_group(backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 148, in init_process_group
+    torch.distributed.init_process_group(backend, timeout=timeout, init_method=init_method)
+  File "/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/torch_overwrites.py", line 259, in wrap_init_process_group
+    return init_process_group_orig(
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/c10d_logger.py", line 74, in wrapper
+    func_return = func(*args, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 1141, in init_process_group
+    store, rank, world_size = next(rendezvous_iterator)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 241, in _env_rendezvous_handler
+    store = _create_c10d_store(master_addr, master_port, rank, world_size, timeout)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 172, in _create_c10d_store
+    return TCPStore(
+TimeoutError: The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+[E socket.cpp:922] [c10d] The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+Traceback (most recent call last):
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+    pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/training.py", line 162, in pretrain
+    initialize_megatron(extra_args_provider=extra_args_provider,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 95, in initialize_megatron
+    finish_mpu_init()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 77, in finish_mpu_init
+    _initialize_distributed()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 276, in _initialize_distributed
+    deepspeed.init_distributed(dist_backend=args.distributed_backend)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/comm.py", line 670, in init_distributed
+    cdb = TorchBackend(dist_backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 120, in __init__
+    self.init_process_group(backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 148, in init_process_group
+    torch.distributed.init_process_group(backend, timeout=timeout, init_method=init_method)
+  File "/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/torch_overwrites.py", line 259, in wrap_init_process_group
+    return init_process_group_orig(
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/c10d_logger.py", line 74, in wrapper
+    func_return = func(*args, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 1141, in init_process_group
+    store, rank, world_size = next(rendezvous_iterator)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 241, in _env_rendezvous_handler
+    store = _create_c10d_store(master_addr, master_port, rank, world_size, timeout)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 172, in _create_c10d_store
+    return TCPStore(
+TimeoutError: The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+[E socket.cpp:922] [c10d] The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+Traceback (most recent call last):
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+    pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/training.py", line 162, in pretrain
+    initialize_megatron(extra_args_provider=extra_args_provider,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 95, in initialize_megatron
+    finish_mpu_init()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 77, in finish_mpu_init
+    _initialize_distributed()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 276, in _initialize_distributed
+    deepspeed.init_distributed(dist_backend=args.distributed_backend)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/comm.py", line 670, in init_distributed
+    cdb = TorchBackend(dist_backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 120, in __init__
+    self.init_process_group(backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 148, in init_process_group
+    torch.distributed.init_process_group(backend, timeout=timeout, init_method=init_method)
+  File "/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/torch_overwrites.py", line 259, in wrap_init_process_group
+    return init_process_group_orig(
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/c10d_logger.py", line 74, in wrapper
+    func_return = func(*args, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 1141, in init_process_group
+    store, rank, world_size = next(rendezvous_iterator)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 241, in _env_rendezvous_handler
+    store = _create_c10d_store(master_addr, master_port, rank, world_size, timeout)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 172, in _create_c10d_store
+    return TCPStore(
+TimeoutError: The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+[E socket.cpp:922] [c10d] The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+Traceback (most recent call last):
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+    pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/training.py", line 162, in pretrain
+    initialize_megatron(extra_args_provider=extra_args_provider,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 95, in initialize_megatron
+    finish_mpu_init()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 77, in finish_mpu_init
+    _initialize_distributed()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 276, in _initialize_distributed
+    deepspeed.init_distributed(dist_backend=args.distributed_backend)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/comm.py", line 670, in init_distributed
+    cdb = TorchBackend(dist_backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 120, in __init__
+    self.init_process_group(backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 148, in init_process_group
+    torch.distributed.init_process_group(backend, timeout=timeout, init_method=init_method)
+  File "/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/torch_overwrites.py", line 259, in wrap_init_process_group
+    return init_process_group_orig(
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/c10d_logger.py", line 74, in wrapper
+    func_return = func(*args, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 1141, in init_process_group
+    store, rank, world_size = next(rendezvous_iterator)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 241, in _env_rendezvous_handler
+    store = _create_c10d_store(master_addr, master_port, rank, world_size, timeout)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 172, in _create_c10d_store
+    return TCPStore(
+TimeoutError: The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+[E socket.cpp:922] [c10d] The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+Traceback (most recent call last):
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+    pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/training.py", line 162, in pretrain
+    initialize_megatron(extra_args_provider=extra_args_provider,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 95, in initialize_megatron
+    finish_mpu_init()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 77, in finish_mpu_init
+    _initialize_distributed()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 276, in _initialize_distributed
+    deepspeed.init_distributed(dist_backend=args.distributed_backend)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/comm.py", line 670, in init_distributed
+    cdb = TorchBackend(dist_backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 120, in __init__
+    self.init_process_group(backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 148, in init_process_group
+    torch.distributed.init_process_group(backend, timeout=timeout, init_method=init_method)
+  File "/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/torch_overwrites.py", line 259, in wrap_init_process_group
+    return init_process_group_orig(
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/c10d_logger.py", line 74, in wrapper
+    func_return = func(*args, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 1141, in init_process_group
+    store, rank, world_size = next(rendezvous_iterator)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 241, in _env_rendezvous_handler
+    store = _create_c10d_store(master_addr, master_port, rank, world_size, timeout)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 172, in _create_c10d_store
+    return TCPStore(
+TimeoutError: The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+[E socket.cpp:922] [c10d] The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+Traceback (most recent call last):
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/./pretrain_llama.py", line 110, in <module>
+    pretrain(train_valid_test_datasets_provider, model_provider, forward_step, extra_args_provider=llama_argument_handler,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/training.py", line 162, in pretrain
+    initialize_megatron(extra_args_provider=extra_args_provider,
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 95, in initialize_megatron
+    finish_mpu_init()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 77, in finish_mpu_init
+    _initialize_distributed()
+  File "/Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/megatron/initialize.py", line 276, in _initialize_distributed
+    deepspeed.init_distributed(dist_backend=args.distributed_backend)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/comm.py", line 670, in init_distributed
+    cdb = TorchBackend(dist_backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 120, in __init__
+    self.init_process_group(backend, timeout, init_method, rank, world_size)
+  File "/usr/local/lib/python3.10/dist-packages/deepspeed/comm/torch.py", line 148, in init_process_group
+    torch.distributed.init_process_group(backend, timeout=timeout, init_method=init_method)
+  File "/usr/local/lib/python3.10/dist-packages/habana_frameworks/torch/core/torch_overwrites.py", line 259, in wrap_init_process_group
+    return init_process_group_orig(
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/c10d_logger.py", line 74, in wrapper
+    func_return = func(*args, **kwargs)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 1141, in init_process_group
+    store, rank, world_size = next(rendezvous_iterator)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 241, in _env_rendezvous_handler
+    store = _create_c10d_store(master_addr, master_port, rank, world_size, timeout)
+  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/rendezvous.py", line 172, in _create_c10d_store
+    return TCPStore(
+TimeoutError: The client socket has timed out after 1800s while trying to connect to (100.83.134.158, 29500).
+[2024-04-17 14:06:29,834] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 2748
+[2024-04-17 14:06:29,931] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 2749
+[2024-04-17 14:06:29,931] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 2750
+[2024-04-17 14:06:29,932] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 2751
+[2024-04-17 14:06:29,984] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 2752
+[2024-04-17 14:06:29,985] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 2753
+[2024-04-17 14:06:30,037] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 2754
+[2024-04-17 14:06:30,037] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 2755
+[2024-04-17 14:06:30,037] [ERROR] [launch.py:322:sigkill_handler] ['/usr/bin/bash', '-c', '     cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed &&     python3 -u ./pretrain_llama.py     --deepspeed     --tensor-model-parallel-size 1     --pipeline-model-parallel-size 1     --position-embedding-type rotary     --no-bias     --layernorm-type rmsnorm     --activation-func-type swiglu     --layernorm-epsilon 1e-6     --num-layers 16     --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/llama13b_x//tensorboard     --log-validation-ppl-to-tensorboard     --log-batch-size-to-tensorboard     --log-timers-to-tensorboard     --load /data/output/llama13b_x//checkpoints_zero_stage_2     --deepspeed_config=/data/output/llama13b_x//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/llama13b_x//checkpoints_zero_stage_2 --hf-save /data/output/llama13b_x//hf_ckpt --save-interval 100 --verify-checkpoint --verify-checkpoint-model-type LLAMA'] exits with return code = 1

univ_ckpt_new/zero/10.attention.dense.weight/exp_avg.pt

@@ -0,0 +1,3 @@
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+size 16778460