code: def track_min_max_val(
      self, wrapper: ModuleWrapper, target_name: str, target: Tensor
  ):
      # in a fused compression pipeline, the target name may be another compressor's target name
      if not wrapper.training or not self.check_target(
          wrapper, target_name
      ):
          return
      return track_min_max_val(wrapper, target_name, target)
  
imports: from __future__ import annotations
  from typing import Dict, List, 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 7 for calling the QATQuantizer obj's underlying member method code with example usage: obj.track_min_max_val(wrapper, target_name, target) and returns: track_min_max_val