code: def test_hyperband_integration(tmp_path):
      tuner = hyperband_module.Hyperband(
          objective="val_loss",
          hypermodel=build_model,
          hyperband_iterations=2,
          max_epochs=6,
          factor=3,
          directory=tmp_path,
      )
  
      x, y = np.ones((2, INPUT_DIM)), np.ones((2, 1))
      tuner.search(x, y, validation_data=(x, y))
  
      # Make sure Oracle is registering new HPs.
      updated_hps = tuner.oracle.get_space().values
      assert "units1" in updated_hps
      assert "bias1" in updated_hps
  
      best_score = tuner.oracle.get_best_trials()[0].score
      best_model = tuner.get_best_models()[0]
      assert best_model.evaluate(x, y) == best_score
  
file_path: keras-tuner/keras_tuner/tuners/hyperband_test.py
imports: import numpy
  import pytest
  import keras_tuner
  from keras_tuner import backend
  from keras_tuner import utils
  from keras_tuner.backend import keras
  from keras_tuner.engine import tuner_utils
  from keras_tuner.tuners import hyperband
label_desc: Use image node_id 5 for calling a global function with example usage: test_hyperband_integration(tmp_path) without return types