code: def init_scale_zp(
      self, wrapper: ModuleWrapper, target_name: str, target: Tensor
  ):
      if self.is_init or not self.check_target(wrapper, target_name):
          return
      target_space = wrapper.quantization_target_spaces[target_name]
      target_space.zero_point = torch.tensor(0.0).to(target.device)
      target_space.scale = torch.tensor(1.0).to(target.device)
  
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 ..base.target_space import TargetType
  from ..utils import Evaluator, _EVALUATOR_DOCSTRING
label_desc: Use image node_id 8 for calling the BNNQuantizer obj's underlying member method code with example usage: obj.init_scale_zp(wrapper, target_name, target) without return types