code: def get_transformer_state(self, tp_index: int, pp_index: int) -> list:
      assert tp_index < self.tp_degree
      assert pp_index < self.pp_degree
      t_list = []
      for fname_list in self.transformer_file_map[(tp_index, pp_index)]:
          sd_list = [
              torch.load(fname, map_location=torch.device("cpu"))
              for fname in fname_list
          ]
          sd = self._merge_state_dicts(sd_list)
          t_list.append(sd)
      return t_list
  
imports: import os
  from typing import Dict
  import torch
  from .reshape_3d_utils import model_3d_desc
  from .reshape_utils import basic_folder_validation, merge_state, partition_data, get_files, get_files_with_prefix
  from .constants import MODEL_FILE_PREFIX, LAYER_FILE_PREFIX
  from .reshape_meg_2d import reshape_meg_2d_parallel, meg_2d_parallel_map
  from .zero_checkpoint import ZeROCheckpoint
  from .constants import *
label_desc: Use image node_id 22 for calling the DeepSpeedCheckpoint obj's underlying member method code with example usage: obj.get_transformer_state(tp_index, pp_index) and returns: t_list