code: def merge_state(state_a, state_b, key_list=[]):
      if type(state_a) != type(state_b):
          key_list_string = _key_list_to_string(key_list)
          print(f"key_list = {key_list_string}")
          raise ValueError(
              f"Cannot merge two states of types {type(state_a)} and type {type(state_b)}"
          )
  
      if type(state_a) in (dict, OrderedDict):
          return merge_state_dict(state_a, state_b, key_list)
      elif type(state_a) in (list, tuple):
          return type(state_a)(
              merge_state_list(state_a, state_b, key_list)
          )
      elif torch.is_tensor(state_a):
          return torch.cat([state_a, state_b], 0)
      else:
          return state_a
  
file_path: DeepSpeed/deepspeed/checkpoint/reshape_utils.py
imports: import os
  import torch
  from collections import OrderedDict
  from .constants import ZERO_FILE_PREFIX, FP16_ZERO_FILE_PREFIX, BF16_ZERO_FILE_PREFIX
label_desc: Use image node_id 10 for calling a global function with example usage: merge_state(state_a, state_b, key_list) and returns: merge_state_dict, type, torch, state_a