code: def test_convert_to_metrics_with_list_of_floats():
      assert tuner_utils.convert_to_metrics_dict(
          [0.1, 0.2],
          obj_module.Objective("val_loss", "min"),
      ) == {"val_loss": (0.1 + 0.2) / 2}
  
file_path: keras-tuner/keras_tuner/engine/tuner_utils_test.py
imports: import os
  import numpy
  import pytest
  from keras_tuner.backend import keras
  from keras_tuner.engine import objective
  from keras_tuner.engine import tuner_utils
label_desc: Use image node_id 7 for calling a global function with example usage: test_convert_to_metrics_with_list_of_floats() without return types