class_docstr: Wrap a HPO tuner as a NAS strategy.
  
  Currently we only support:
  
  - Search space with choices.
  - Calling the tuner's ``generate_parameters`` method to generate new models.
  - Calling the tuner's ``receive_trial_result`` method to report the results of models.
  
  We don't support advanced features like checkpointing, resuming, or customized trials.
  
  Parameters
  ----------
  tuner
      A HPO tuner.
class_docstr_tok: ["Wrap","a","HPO","tuner","as","a","NAS","strategy",".","Currently","we","only","support",":","-","Search","space","with","choices",".","-","Calling","the","tuner","'s","``","generate_parameters","``","method","to","generate","new","models",".","-","Calling","the","tuner","'s","``","receive_trial_result","``","method","to","report","the","results","of","models",".","We","do","n't","support","advanced","features","like","checkpointing",",","resuming",",","or","customized","trials",".","Parameters","--","--","--","--","--","tuner","A","HPO","tuner","."]
code: def load_state_dict(self, state_dict: dict) -> None:
      self._model_count = state_dict.get("model_count", 0)
      if self._model_count > 0:
          _logger.warning(
              "Loaded %d previously submitted models, but they are not recorded, or reported to tuner."
          )
  
imports: from __future__ import annotations
  import logging
  import time
  import threading
  from typing import cast
  import nni
  from nni.nas.execution import ExecutionEngine
  from nni.nas.execution.event import FinalMetricEvent, TrainingEndEvent, ModelEventType
  from nni.nas.space import ExecutableModelSpace, ModelStatus
  from nni.tuner import Tuner
  from nni.typehint import SearchSpace
  from .base import Strategy
label_desc: Use image node_id 8 for calling the HPOTunerStrategy obj's underlying member method code with example usage: obj.load_state_dict(state_dict) without return types