code: def register_trigger(self, evaluator: Evaluator):
      def optimizer_task():
          self.current_step += 1
          if self.current_step == self.quant_start_step:
              self.register_qat_apply_method()
  
      evaluator.patch_optimizer_step(
          before_step_tasks=[], after_step_tasks=[optimizer_task]
      )
  
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 10 for calling the QATQuantizer obj's underlying member method code with example usage: obj.register_trigger(evaluator) without return types