def METHOD_NAME():
    valid_input = np.array(
        [1, 2, 4, 3, 8, 6, 7, 5, 9, 10, 12, 11, 13, 16, 15, 14]
    ).astype(np.float32)
    valid_input = np.reshape(valid_input, (1, 4, 4, 1))
    updates, indices = tf.nn.max_pool_with_argmax(
        valid_input, ksize=[2, 2], strides=[2, 2], padding="SAME"
    )
    expected_output = np.array(
        [0, 0, 0, 0, 8, 0, 7, 0, 0, 0, 0, 0, 0, 16, 15, 0]
    ).astype(np.float32)
    expected_output = np.reshape(expected_output, valid_input.shape)
    output = MaxUnpooling2DV2(valid_input.shape)(updates, indices).numpy()
    np.testing.assert_array_equal(expected_output, output)