code: def _register_trigger(self, evaluator: Evaluator):
      self._current_step = 0
      self._remaining_times = self.total_times
  
      def optimizer_task():
          self._current_step += 1
          if self._current_step == self.interval_steps:
              self._remaining_times -= 1
              self.update_sparse_goals(
                  self.total_times - self._remaining_times
              )
              debug_msg = f"{self.__class__.__name__} generate masks, remaining times {self._remaining_times}"
              _logger.debug(debug_msg)
              if self._remaining_times > 0:
                  self._current_step = 0
  
      evaluator.patch_optimizer_step(
          before_step_tasks=[], after_step_tasks=[optimizer_task]
      )
  
imports: from __future__ import annotations
  from collections import defaultdict
  import logging
  from typing import Dict, List
  import torch
  from ..base.compressor import Pruner
  from ..base.wrapper import ModuleWrapper
  from ..utils import Evaluator, _EVALUATOR_DOCSTRING
  from .basic_pruner import LevelPruner, L1NormPruner, L2NormPruner, FPGMPruner
  from .slim_pruner import SlimPruner
  from .taylor_pruner import TaylorPruner
label_desc: Use image node_id 4 for calling the _ComboPruner obj's underlying member method code with example usage: obj._register_trigger(evaluator) without return types