code: def register_ptq_apply_method(self):
      for _, ts in self._target_spaces.items():
          for _, target_space in ts.items():
              target_space.apply_method = (
                  "clamp_round" if self.is_compressed else "bypass"
              )
  
imports: from __future__ import annotations
  from typing import List, Dict, Union, overload
  import torch
  from torch import Tensor
  from ..base.compressor import Compressor, Quantizer
  from ..base.wrapper import ModuleWrapper
  from ..base.target_space import QuantizationTargetSpace
  from ..utils import Evaluator, _EVALUATOR_DOCSTRING
label_desc: Use image node_id 5 for calling the PtqQuantizer obj's underlying member method code with example usage: obj.register_ptq_apply_method() without return types