code: def _get_scale_type(sampling):
      """Returns scale_type in Vizier study_config."""
      if sampling == _SAMPLING_LINEAR:
          return {"scale_type": _LINEAR_SCALE}
      if sampling == _SAMPLING_LOG:
          return {"scale_type": _LOG_SCALE}
      if sampling == _SAMPLING_REVERSE_LOG:
          return {"scale_type": _REVERSE_LOG_SCALE}
      return {"scale_type": _SCALE_TYPE_UNSPECIFIED}
  
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 9 for calling a global function with example usage: _get_scale_type(sampling) and returns: dict, dict, dict, dict