code: def __init__(
      self,
      model: torch.nn.Module,
      config_list: List[Dict],
      evaluator: Evaluator,
      quant_start_step: int = 0,
      existed_wrappers: Dict[str, ModuleWrapper] | None = None,
  ):
      ...
  
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 2 to create a new QATQuantizer object from inherited base classes: Quantizer with example: obj = QATQuantizer(model, config_list, evaluator, quant_start_step, existed_wrappers)