def METHOD_NAME(self):
    input_image = tf.random.uniform((2, 512, 512, 3))
    bounding_boxes = {
        "boxes": tf.ragged.constant(
            [
                [[200, 200, 400, 400], [100, 100, 300, 300]],
                [[200, 200, 400, 400]],
            ],
            dtype=tf.float32,
        ),
        "classes": tf.ragged.constant(
            [
                [
                    0,
                    0,
                ],
                [0],
            ],
            dtype=tf.float32,
        ),
    }
    input = {"images": input_image, "bounding_boxes": bounding_boxes}
    layer = RandomRotation(factor=(0.5, 0.5), bounding_box_format="xyxy")
    output = layer(input)
    expected_output = {
        "boxes": tf.ragged.constant(
            [
                [
                    [112.0, 112.0, 312.0, 312.0],
                    [212.0, 212.0, 412.0, 412.0],
                ],
                [[112.0, 112.0, 312.0, 312.0]],
            ],
            dtype=tf.float32,
        ),
        "classes": tf.ragged.constant(
            [
                [
                    0,
                    0,
                ],
                [0],
            ],
            dtype=tf.float32,
        ),
    }
    expected_output = bounding_box.to_dense(expected_output)
    output["bounding_boxes"] = bounding_box.to_dense(
        output["bounding_boxes"]
    )
    self.assertAllClose(
        expected_output["boxes"], output["bounding_boxes"]["boxes"]
    )
    self.assertAllClose(
        expected_output["classes"],
        output["bounding_boxes"]["classes"],
    )