Class version of AUROC metric
🚀 Feature

Class version of AUROC metric following the v1.x.x standard, so we can do:
auroc = AUROC(num_classes=4)
auroc(pred, target)
auroc.compute()
Motivation

Class based Metrics can be nicer to use in the PyTorch Lightning workflow, so why not add one for AUROC?
Pitch

AUROC will automatically use the correct functional function, auroc or multiclass_auroc, based on whether num_classes == 2 or num_classes > 2, respectively.
Not sure why auroc or multiclass_auroc are 2 separate functions?
Alternatives

Implement the AUROC Metric yourself.
Additional context

Considerations:
How to handle update()? While it's true that most likely the whole dataset will include all classes in pred and targets, this cannot be assumed for a single batch.