code: def __init__(self, ckpt_list, version, checkpoint_engine):
      super().__init__(ckpt_list, version, checkpoint_engine)
      """
          ## Q/K/V data need special processing
          key: transformer.layers.0.attention.query_key_value.weight, shape: torch.Size([3192, 4256])
          key: transformer.layers.0.attention.query_key_value.bias, shape: torch.Size([3192])
  
          ## merge or split on axis=0
          key: word_embeddings.weight, shape: torch.Size([12672, 4256])
          key: transformer.layers.0.mlp.dense_h_to_4h.bias, shape: torch.Size([4256])
          key: transformer.layers.0.mlp.dense_h_to_4h.weight, shape: torch.Size([4256, 4256])
  
          ## merge or split on axis=1
          key: transformer.layers.0.attention.dense.weight, shape: torch.Size([4256, 1064])
          key: transformer.layers.0.mlp.dense_4h_to_h.weight, shape: torch.Size([4256, 4256])
  
          ## no change required
          key: transformer.layers.0.mlp.dense_4h_to_h.bias, shape: torch.Size([4256])
          key: transformer.final_layernorm.weight, shape: torch.Size([4256])
          key: transformer.final_layernorm.bias, shape: torch.Size([4256])
          key: transformer.layers.0.attention.dense.bias, shape: torch.Size([4256])
          key: transformer.layers.0.post_attention_layernorm.weight, shape: torch.Size([4256])
          key: transformer.layers.0.post_attention_layernorm.bias, shape: torch.Size([4256])
          key: transformer.layers.0.input_layernorm.weight, shape: torch.Size([4256])
          key: transformer.layers.0.input_layernorm.bias, shape: torch.Size([4256])
          key: position_embeddings.weight, shape: torch.Size([1024, 4256])
          """
  
imports: import torch
  import os
  import copy
  import collections
  import json
  from abc import ABC, abstractmethod
  from deepspeed.utils import logger
  from deepspeed.runtime.checkpoint_engine.torch_checkpoint_engine import TorchCheckpointEngine
  from .weight_quantizer import WeightQuantization
label_desc: Use image node_id 1 to create a new MegatronSDLoader object from inherited base classes: SDLoaderBase with example: obj = MegatronSDLoader(ckpt_list, version, checkpoint_engine)