code: def patch_optimizer_param_group(self):
      module_name_param_dict = super().patch_optimizer_param_group()
      for module_name, ts in self._target_spaces.items():
          for _, target_space in ts.items():
              if module_name not in module_name_param_dict:
                  module_name_param_dict[module_name] = []
              module_name_param_dict[module_name].append(
                  target_space.scale
              )
              module_name_param_dict[module_name].append(
                  target_space.zero_point
              )
  
      return module_name_param_dict
  
imports: from __future__ import annotations
  import logging
  from typing import List, Dict, overload
  import torch
  from torch import Tensor
  from ..base.compressor import Compressor, Quantizer
  from ..base.wrapper import ModuleWrapper
  from ..utils import Evaluator, _EVALUATOR_DOCSTRING
label_desc: Use image node_id 10 for calling the LsqPlusQuantizer obj's underlying member method code with example usage: obj.patch_optimizer_param_group() and returns: module_name_param_dict