code: def from_compressor(
      cls,
      compressor: Compressor,
      new_config_list: List[Dict],
      quant_start_step: int = 0,
      evaluator: Evaluator | None = None,
  ):
      return super().from_compressor(
          compressor,
          new_config_list,
          quant_start_step=quant_start_step,
          evaluator=evaluator,
      )
  
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 4 for calling the QATQuantizer obj's underlying member method code with example usage: obj.from_compressor(cls, compressor, new_config_list, quant_start_step, evaluator) and returns: super