def METHOD_NAME(vec) -> None:
    forward_cumsum = cumsum(mx.nd, mx.nd.array(vec)).asnumpy()
    np_forward_cumsum = np.cumsum(vec, axis=-1)
    assert np.all(forward_cumsum == np_forward_cumsum), (
        f"forward cumsum did not match: "
        f"expected: {np_forward_cumsum}, obtained: {forward_cumsum}"
    )
    reverse_cumsum = cumsum(mx.nd, mx.nd.array(vec), reverse=True).asnumpy()
    np_reverse_cumsum = np.flip(
        np.cumsum(np.flip(vec, axis=-1), axis=-1), axis=-1
    )
    assert np.all(reverse_cumsum == np_reverse_cumsum), (
        f"reverse cumsum did not match: "
        f"expected: {np_reverse_cumsum}, obtained: {reverse_cumsum}"
    )
    forward_cumsum_excl = cumsum(
        mx.nd, mx.nd.array(vec), exclusive=True
    ).asnumpy()
    np_forward_cumsum_excl = np.insert(
        np_forward_cumsum[..., :-1], 0, 0, axis=-1
    )
    assert np.all(forward_cumsum_excl == np_forward_cumsum_excl), (
        f"forward cumsum (exclusive) did not match: "
        f"expected: {np_forward_cumsum_excl}, obtained: {forward_cumsum_excl}"
    )
    reverse_cumsum_excl = cumsum(
        mx.nd, mx.nd.array(vec), exclusive=True, reverse=True
    ).asnumpy()
    np_reverse_cumsum_excl = np.insert(
        np_reverse_cumsum[..., 1:], np.shape(vec)[-1] - 1, 0, axis=-1
    )
    assert np.all(reverse_cumsum_excl == np_reverse_cumsum_excl), (
        f"reverse cumsum (exclusive) did not match: "
        f"expected: {np_reverse_cumsum_excl}, obtained: {reverse_cumsum_excl}"
    )