code: def _compare_prepare_convert_qconfig_mappings(
      prepare_qconfig_mapping: QConfigMapping,
      convert_qconfig_mapping: QConfigMapping,
  ):
      r"""Compare the qconfig_mapping passed in convert to the one from prepare and check the values
  
      Args:
        `prepare_qconfig_mapping`: configuration for prepare quantization step
        `convert_qconfig_mapping`: configuration for convert quantization step
      """
      assert qconfig_equals(
          prepare_qconfig_mapping.global_qconfig,
          convert_qconfig_mapping.global_qconfig,
      ), "Expected global qconfigs to be the same in the prepare and convert quantization configs"
      prepare_dicts: List[OrderedDict] = [
          prepare_qconfig_mapping.object_type_qconfigs,
          prepare_qconfig_mapping.module_name_qconfigs,
          prepare_qconfig_mapping.module_name_regex_qconfigs,
      ]
      convert_dicts: List[OrderedDict] = [
          convert_qconfig_mapping.object_type_qconfigs,
          convert_qconfig_mapping.module_name_qconfigs,
          convert_qconfig_mapping.module_name_regex_qconfigs,
      ]
      dict_names = [
          _OBJECT_TYPE_DICT_KEY,
          _MODULE_NAME_DICT_KEY,
          _MODULE_NAME_REGEX_DICT_KEY,
      ]
      for i in range(len(prepare_dicts)):
          for name in prepare_dicts[i].keys():
              assert (
                  name in convert_dicts[i]
              ), f"Missing key {dict_names[i]} {name} in convert QConfigMapping \
                  when it was present in prepare"
              assert convert_dicts[i][name] is None or qconfig_equals(
                  prepare_dicts[i][name], convert_dicts[i][name]
              ), f"Expected convert QConfigMapping to have the same qconfig as prepare for key {dict_names[i]} {name}; \
                  prepare: {prepare_dicts[i][name]}; convert: {convert_dicts[i][name]}"
  
imports: import torch
  import re
  from collections import defaultdict, OrderedDict
  from typing import Callable, Any, Dict, Tuple, Set, List, Union
  from torch.ao.quantization import QConfig
  from torch.ao.quantization.qconfig import _add_module_to_qconfig_obs_ctr, QConfigAny, qconfig_equals
  from torch.ao.quantization.observer import _is_activation_post_process
  from torch.ao.quantization.backend_config import BackendConfig, DTypeConfig
  from torch.ao.quantization.backend_config.utils import get_module_to_qat_module
  from torch.fx import GraphModule
  from torch.fx.graph import Graph
  from torch.ao.nn.intrinsic import _FusedModule
  from ..utils import _parent_name, get_qconfig_dtypes
  from ..qconfig_mapping import _OBJECT_TYPE_DICT_KEY, _MODULE_NAME_DICT_KEY, _MODULE_NAME_REGEX_DICT_KEY, QConfigMapping
label_desc: Use image node_id 5 for calling a global function with example usage: _compare_prepare_convert_qconfig_mappings(prepare_qconfig_mapping, convert_qconfig_mapping) without return types