code: def test_model_construction_rand_aug():
      hp = hp_module.HyperParameters()
      hm = aug_module.HyperImageAugment(
          input_shape=(None, None, 3), rotate=[0.2, 0.5]
      )
      model = hm.build(hp)
      assert model.layers
      assert model.name == "image_rand_augment"
  
      # Output shape includes batch dimension.
      assert model.output_shape == (None, None, None, 3)
      out = model.predict(np.ones((1, 32, 32, 3)))
      assert out.shape == (1, 32, 32, 3)
      # Augment does not distort image when inferencing.
      assert (out != 1).sum() == 0
  
file_path: keras-tuner/keras_tuner/applications/augment_test.py
imports: import numpy
  import pytest
  from keras_tuner.applications import augment
  from keras_tuner.backend import config
  from keras_tuner.backend import keras
  from keras_tuner.engine import hyperparameters
label_desc: Use image node_id 5 for calling a global function with example usage: test_model_construction_rand_aug() without return types