def METHOD_NAME(quantile_weights, correct_qt_loss) -> None:
    y_true = nd.ones(shape=(10, 10, 10))
    y_pred = nd.zeros(shape=(10, 10, 10, 2))
    quantiles = [0.5, 0.9]
    loss = QuantileLoss(quantiles, quantile_weights)
    tol = 1e-5
    if not quantile_weights:
        for idx, q in enumerate(quantiles):
            assert (
                nd.mean(
                    loss.compute_quantile_loss(
                        nd.ndarray, y_true, y_pred[:, :, :, idx], q
                    )
                )
                - correct_qt_loss[idx]
                < tol
            ), f"computing quantile loss at quantile {q} fails!"
    else:
        assert (
            nd.mean(loss(y_true, y_pred)) - correct_qt_loss < tol
        ), "computing weighted quantile loss fails!"