class_docstr: TFX Tuner executor impl as a worker in a Google Cloud AI Platform job.
class_docstr_tok: ["TFX","Tuner","executor","impl","as","a","worker","in","a","Google","Cloud","AI","Platform","job","."]
code: def Do(
      self,
      input_dict: Dict[str, List[types.Artifact]],
      output_dict: Dict[str, List[types.Artifact]],
      exec_properties: Dict[str, Any],
  ) -> None:
      tuner = self._search(input_dict, output_dict, exec_properties)
  
      if self._tuner_id is not None and not self._is_chief:
          logging.info("Returning since this is not chief worker.")
          return
  
      tuner_executor.write_best_hyperparameters(tuner, output_dict)
  
imports: import datetime
  import json
  import os
  from typing import Any, Dict, List
  from absl import logging
  from tfx import types
  from tfx.components.tuner import executor
  from tfx.dsl.components.base import base_executor
  from tfx.extensions.google_cloud_ai_platform import constants
  from tfx.extensions.google_cloud_ai_platform import runner
  from tfx.extensions.google_cloud_ai_platform.trainer import executor
  from tfx.types import standard_component_specs
  from tfx.utils import doc_controls
  from tfx.utils import json_utils
  from tfx.utils import name_utils
  import multiprocessing
label_desc: Use image node_id 5 for calling the _WorkerExecutor obj's underlying member method code with example usage: obj.Do(input_dict, output_dict, exec_properties) without return types