def METHOD_NAME(self):
    img_shape = (4, 4, 3)
    xs = tf.stack(
        [2 * np.ones(img_shape), np.ones(img_shape)],
        axis=0,
    )
    xs = tf.cast(xs, tf.float32)
    fill_value = 0.0
    layer = preprocessing.RandomCutout(
        height_factor=(0.4, 0.9),
        width_factor=(0.1, 0.3),
        fill_mode="constant",
        fill_value=fill_value,
        seed=1,
    )
    xs = layer(xs)
    # Some pixels should be replaced with fill value
    self.assertTrue(tf.math.reduce_any(xs[0] == fill_value))
    self.assertTrue(tf.math.reduce_any(xs[0] == 2.0))
    self.assertTrue(tf.math.reduce_any(xs[1] == fill_value))
    self.assertTrue(tf.math.reduce_any(xs[1] == 1.0))