Delete conversion_to_hf.log

conversion_to_hf.log

@@ -1,109 +0,0 @@
-Loaded loader_megatron_core as the loader.
-Loaded saver_llama2_hf_bf as the saver.
-Starting saver...
-Starting loader...
-fused_indices_to_multihot has reached end of life. Please migrate to a non-experimental function.
-/usr/local/lib/python3.12/dist-packages/modelopt/torch/utils/import_utils.py:31: UserWarning: Failed to import apex plugin due to: AttributeError("module 'transformers.modeling_utils' has no attribute 'Conv1D'"). You may ignore this warning if you do not need this plugin.
-  warnings.warn(
-/usr/local/lib/python3.12/dist-packages/modelopt/torch/utils/import_utils.py:31: UserWarning: Failed to import huggingface plugin due to: AttributeError("module 'transformers.modeling_utils' has no attribute 'Conv1D'"). You may ignore this warning if you do not need this plugin.
-  warnings.warn(
-/usr/local/lib/python3.12/dist-packages/modelopt/torch/utils/import_utils.py:31: UserWarning: Failed to import megatron plugin due to: AttributeError("module 'transformers.modeling_utils' has no attribute 'Conv1D'"). You may ignore this warning if you do not need this plugin.
-  warnings.warn(
-Setting num_layers to 14 from checkpoint
-Setting hidden_size to 5120 from checkpoint
-Setting ffn_hidden_size to 27648 from checkpoint
-Setting seq_length to 131072 from checkpoint
-Setting num_attention_heads to 40 from checkpoint
-Setting num_query_groups to 8 from checkpoint
-Setting group_query_attention to True from checkpoint
-Setting kv_channels to 128 from checkpoint
-Setting max_position_embeddings to 131072 from checkpoint
-Setting position_embedding_type to rope from checkpoint
-Setting add_position_embedding to True from checkpoint
-Setting use_rotary_position_embeddings to True from checkpoint
-Setting rotary_base to 500000 from checkpoint
-Setting rotary_percent to 1.0 from checkpoint
-Setting rotary_interleaved to False from checkpoint
-Setting add_bias_linear to False from checkpoint
-Setting add_qkv_bias to False from checkpoint
-Setting squared_relu to False from checkpoint
-Setting swiglu to True from checkpoint
-Setting untie_embeddings_and_output_weights to True from checkpoint
-Setting apply_layernorm_1p to False from checkpoint
-Setting normalization to RMSNorm from checkpoint
-Setting apply_query_key_layer_scaling to False from checkpoint
-Setting attention_dropout to 0.0 from checkpoint
-Setting hidden_dropout to 0.0 from checkpoint
-Checkpoint did not provide arguments hybrid_override_pattern
-Checkpoint did not provide arguments spec
-Setting hybrid_attention_ratio to 0.0 from checkpoint
-Setting hybrid_mlp_ratio to 0.0 from checkpoint
-Checkpoint did not provide arguments num_experts
-Setting moe_layer_freq to 1 from checkpoint
-Setting moe_router_topk to 2 from checkpoint
-Setting moe_router_pre_softmax to False from checkpoint
-Setting moe_grouped_gemm to False from checkpoint
-Checkpoint did not provide arguments moe_shared_expert_intermediate_size
-Setting mamba_state_dim to 128 from checkpoint
-Setting mamba_head_dim to 64 from checkpoint
-Setting mamba_num_groups to 8 from checkpoint
-Checkpoint did not provide arguments mamba_num_heads
-Setting is_hybrid_model to False from checkpoint
-Checkpoint did not provide arguments heterogeneous_layers_config_path
-Checkpoint did not provide arguments heterogeneous_layers_config_encoded_json
-Setting tokenizer_type to SFTTokenizer from checkpoint
-Setting tokenizer_model to /cpfs01/users/wzhang/iquest-coder-v1.1/RepoData-Ucoder-32B-128k-from2.5.2/97.09B_instruct_iquest-coder from checkpoint
-Checkpoint did not provide arguments tiktoken_pattern
-Setting padded_vocab_size to 76800 from checkpoint
-INFO:megatron.core.num_microbatches_calculator:setting number of microbatches to constant 1
-WARNING: one_logger package is required to enable e2e metrics tracking. please go to https://confluence.nvidia.com/display/MLWFO/Package+Repositories for details to install it
-building GPT model ...
-(TP, PP) mismatch after resume ((1, 1) vs (8, 1) from checkpoint): RNG state will be ignored
-sharded_state_dict metadata loaded from the checkpoint: {'distrib_optim_sharding_type': 'dp_reshardable', 'singleton_local_shards': False, 'chained_optim_avoid_prefix': True}
-Job sharding has changed: Rerun state will be ignored
- loading distributed checkpoint from /tmp/megatron_convert_iter1717_node0_pid360_aefde564 at iteration 1717
-/volume/pt-train/users/wzhang/wjj-workspace/code-sft/src/training/Megatron-LM/megatron/core/dist_checkpointing/strategies/torch.py:956: FutureWarning: `load_state_dict` is deprecated and will be removed in future versions. Please use `load` instead.
-  checkpoint.load_state_dict(
-/usr/local/lib/python3.12/dist-packages/torch/distributed/checkpoint/planner_helpers.py:406: FutureWarning: Please use DTensor instead and we are deprecating ShardedTensor.
-  device = getattr(value, "device", None)
-/usr/local/lib/python3.12/dist-packages/torch/distributed/checkpoint/default_planner.py:454: FutureWarning: Please use DTensor instead and we are deprecating ShardedTensor.
-  and md.size != obj.size()
- checkpoint version 3.0
-  successfully loaded checkpoint from /tmp/megatron_convert_iter1717_node0_pid360_aefde564 [ t 1/1, p 1/1 ] at iteration 1717
-sending embeddings
-sending transformer layer 0
-sending transformer layer 1
-sending transformer layer 2
-sending transformer layer 3
-sending transformer layer 4
-sending transformer layer 5
-sending transformer layer 6
-sending transformer layer 7
-sending transformer layer 8
-sending transformer layer 9
-sending transformer layer 10
-sending transformer layer 11
-sending transformer layer 12
-sending transformer layer 13
-sending final norm
-sending output layer
-Waiting for saver to complete...
-fused_indices_to_multihot has reached end of life. Please migrate to a non-experimental function.
-received embeddings
-received transformer layer 0
-received transformer layer 1
-received transformer layer 2
-received transformer layer 3
-received transformer layer 4
-received transformer layer 5
-received transformer layer 6
-received transformer layer 7
-received transformer layer 8
-received transformer layer 9
-received transformer layer 10
-received transformer layer 11
-received transformer layer 12
-received transformer layer 13
-received final norm
-received output layer
-Saving model to disk ...