    ...                       [0.05, 0.55, 0.75],
        ...                       [0.05, 0.65, 0.05]])
        >>> target = torch.tensor([[1, 0, 1],
        ...                        [0, 0, 0],
        ...                        [0, 1, 1],
        ...                        [1, 1, 1]])
        >>> multilabel_auroc(preds, target, num_labels=3, average="macro", thresholds=None)
        tensor(0.6528)
        >>> multilabel_auroc(preds, target, num_labels=3, average=None, thresholds=None)
        tensor([0.6250, 0.5000, 0.8333])
        >>> multilabel_auroc(preds, target, num_labels=3, average="macro", thresholds=5)
        tensor(0.6528)
        >>> multilabel_auroc(preds, target, num_labels=3, average=None, thresholds=5)
        tensor([0.6250, 0.5000, 0.8333])

    )