code: def convert_study_config_to_objective(
      study_config: Dict[Text, Any]
  ) -> List[oracle_module.Objective]:
      """Converts Vizier study_config to a list of oracle_module.Objective."""
      if not study_config.get("metrics"):
          raise ValueError(
              '"metrics" not found in study_config {}'.format(
                  study_config
              )
          )
      if not isinstance(study_config["metrics"], list):
          raise ValueError(
              'study_config["metrics"] should be a list of {"metric": ...}'
          )
      if not study_config["metrics"][0].get("metric"):
          raise ValueError(
              '"metric" not found in study_config["metrics"][0]'
          )
      return [
          format_objective(m["metric"], format_goal(m["goal"]))[0]
          for m in study_config["metrics"]
      ]
  
imports: from typing import Any, Dict, List, Optional, Text, Union
  from keras_tuner.engine import hyperparameters
  from keras_tuner.engine import metrics_tracking
  from keras_tuner.engine import oracle
  from keras_tuner.engine import trial
  import numpy
  from tensorboard.plugins.hparams import api
label_desc: Use image node_id 2 for calling a global function with example usage: convert_study_config_to_objective(study_config) and returns: unknown