import tensorflow as tf

    )
    self.assertAllClose(
        augmented_tensor_dict_out[fields.InputDataFields.groundtruth_boxes],
        [[10, 10, 20, 20]]
    )
    self.assertAllClose(
        augmented_tensor_dict_out[fields.InputDataFields.groundtruth_keypoints],
        [[[10, 20], [10, 10]]]
    )


def _fake_model_preprocessor_fn(image):
  return (image, tf.expand_dims(tf.shape(image)[1:], axis=0))


def _fake_image_resizer_fn(image, mask):
  return (image, mask, tf.shape(image))


class DataTransformationFnTest(test_case.TestCase):

  def test_combine_additional_channels_if_present(self):
    image = np.random.rand(4, 4, 3).astype(np.float32)
    additional_channels = np.random.rand(4, 4, 2).astype(np.float32)
