code: def patch_optimizer_param_group(self):
      module_name_param_dict = {}
      for module_name, _ in self._target_spaces.items():
          wrapper = self._module_wrappers[module_name]
          if getattr(wrapper, "is_register_bias", False) and isinstance(
              wrapper.bias, torch.nn.parameter.Parameter
          ):
              module_name_param_dict[module_name] = [wrapper.bias]
  
      return module_name_param_dict
  
imports: from __future__ import annotations
  from collections import defaultdict
  from copy import deepcopy
  import logging
  from typing import Any, Dict, List, Literal, Callable
  import torch
  from torch.utils._pytree import tree_map
  from .config import trans_legacy_config_list, default_config_schema
  from .target_space import TargetSpace, TargetType, DistillationTargetSpace, PruningTargetSpace, QuantizationTargetSpace
  from .wrapper import ModuleWrapper, register_wrappers
  from ..utils import Evaluator, Scaling, _EVALUATOR_DOCSTRING
label_desc: Use image node_id 7 for calling the Quantizer obj's underlying member method code with example usage: obj.patch_optimizer_param_group() and returns: module_name_param_dict