code: def test_model_construction(pooling):
      hp = hp_module.HyperParameters()
      hp.Choice("pooling", [pooling])
      hypermodel = xception.HyperXception(
          input_shape=(128, 128, 3), classes=10
      )
      model = hypermodel.build(hp)
      assert hp.values["pooling"] == pooling
      assert model.layers
      assert model.name == "Xception"
      assert model.output_shape == (None, 10)
      model.train_on_batch(np.ones((1, 128, 128, 3)), np.ones((1, 10)))
      out = model.predict(np.ones((1, 128, 128, 3)))
      assert out.shape == (1, 10)
  
file_path: keras-tuner/keras_tuner/applications/xception_test.py
imports: import numpy
  import pytest
  from keras_tuner.applications import xception
  from keras_tuner.backend import config
  from keras_tuner.backend import keras
  from keras_tuner.engine import hyperparameters
label_desc: Use image node_id 1 for calling a global function with example usage: test_model_construction(pooling) without return types