= tensor([2, 1, 0, 0])
        >>> preds = tensor([2, 1, 0, 1])
        >>> multiclass_confusion_matrix(preds, target, num_classes=3)
        tensor([[1, 1, 0],
                [0, 1, 0],
                [0, 0, 1]])

    Example (pred is float tensor):
        >>> from torchmetrics.functional.classification import multiclass_confusion_matrix
        >>> target = tensor([2, 1, 0, 0])
        >>> preds = tensor([[0.16, 0.26, 0.58],
        ...                 [0.22, 0.61, 0.17],
        ...                 [0.71, 0.09, 0.20],
        ...                 [0.05, 0.82, 0.13]])
        >>> multiclass_confusion_matrix(preds, target, num_classes=3)
        tensor([[1, 1, 0],
                [0, 1, 0],
                [0, 0, 1]])

    )