code: def _fuse_postprocess(self, evaluator: Evaluator) -> None:
      self.evaluator.evaluate()
      # compute and update scale and zero
      self.update_scale_zp()
      self.is_compressed = True
      self.register_ptq_apply_method()
      # bias correction
      if self.is_bias_correction:
          self.bias_correction()
  
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 11 for calling the PtqQuantizer obj's underlying member method code with example usage: obj._fuse_postprocess(evaluator) without return types