code: def test_convert_study_config_float(
      self, min_value, max_value, step, sampling, expected_config
  ):
      hps = hp_module.HyperParameters()
      hps.Float(
          "learning_rate",
          min_value=min_value,
          max_value=max_value,
          step=step,
          sampling=sampling,
      )
      study_config = utils.make_study_config(
          objective="accuracy", hyperparams=hps
      )
      self._assert_study_config_equal(study_config, expected_config)
  
      actual_hps = utils.convert_study_config_to_hps(study_config)
      self._assert_hps_equal(actual_hps, hps)
  
imports: import copy
  from absl.testing import parameterized
  from keras_tuner.engine import hyperparameters
  from keras_tuner.engine import oracle
  from keras_tuner.engine import trial
  import tensorflow
  from tensorboard.plugins.hparams import api
  from tensorflow_cloud.tuner.tuner import utils
label_desc: Use image node_id 4 for calling the CloudTunerUtilsTest obj's underlying member method code with example usage: obj.test_convert_study_config_float(min_value, max_value, step, sampling, expected_config) without return types