def METHOD_NAME(inputs):
    """rotate image."""
    inputs_shape = tf.shape(inputs)
    batch_size = inputs_shape[0]
    img_hd = tf.cast(inputs_shape[1], tf.float32)
    img_wd = tf.cast(inputs_shape[2], tf.float32)
    min_angle = LOWER * 2.0 * np.pi
    max_angle = UPPER * 2.0 * np.pi
    angles = tf.random.uniform(
        shape=[batch_size], minval=min_angle, maxval=max_angle
    )
    return image_preprocessing.transform(
        inputs, image_preprocessing.get_rotation_matrix(angles, img_hd, img_wd)
    )