code: def test_random_transforms():
      x = np.random.random((2, 28, 28))
      # Test get_random_transform with predefined seed
      seed = 1
      generator = image_data_generator.ImageDataGenerator(
          rotation_range=90.0,
          width_shift_range=0.1,
          height_shift_range=0.1,
          shear_range=0.5,
          zoom_range=0.2,
          channel_shift_range=0.1,
          brightness_range=(1, 5),
          horizontal_flip=True,
          vertical_flip=True,
      )
      transform_dict = generator.get_random_transform(x.shape, seed)
      transform_dict2 = generator.get_random_transform(
          x.shape, seed * 2
      )
      assert transform_dict["theta"] != 0
      assert transform_dict["theta"] != transform_dict2["theta"]
      assert transform_dict["tx"] != 0
      assert transform_dict["tx"] != transform_dict2["tx"]
      assert transform_dict["ty"] != 0
      assert transform_dict["ty"] != transform_dict2["ty"]
      assert transform_dict["shear"] != 0
      assert transform_dict["shear"] != transform_dict2["shear"]
      assert transform_dict["zx"] != 0
      assert transform_dict["zx"] != transform_dict2["zx"]
      assert transform_dict["zy"] != 0
      assert transform_dict["zy"] != transform_dict2["zy"]
      assert transform_dict["channel_shift_intensity"] != 0
      assert (
          transform_dict["channel_shift_intensity"]
          != transform_dict2["channel_shift_intensity"]
      )
      assert transform_dict["brightness"] != 0
      assert (
          transform_dict["brightness"] != transform_dict2["brightness"]
      )
  
      # Test get_random_transform without any randomness
      generator = image_data_generator.ImageDataGenerator()
      transform_dict = generator.get_random_transform(x.shape, seed)
      assert transform_dict["theta"] == 0
      assert transform_dict["tx"] == 0
      assert transform_dict["ty"] == 0
      assert transform_dict["shear"] == 0
      assert transform_dict["zx"] == 1
      assert transform_dict["zy"] == 1
      assert transform_dict["channel_shift_intensity"] is None
      assert transform_dict["brightness"] is None
  
file_path: keras-preprocessing/tests/image/image_data_generator_test.py
imports: import numpy
  import pytest
  from PIL import Image
  from keras_preprocessing.image import image_data_generator, utils
label_desc: Use image node_id 11 for calling a global function with example usage: test_random_transforms() without return types