Test all metrics against sklearn (with many input trials)
Hand-chosen values are not enough, we need to test with a large batch of inputs where possible.
Something in this style, maybe with a fixed seed:
def test_auroc_versus_sklearn():
    for i in range(100):
        target = torch.randint(0, 2, size=(10, ))
        pred = torch.randint(0, 2, size=(10,))
        score_sk = sklearn.metrics.roc_auc_score(target.numpy(), pred.numpy())  # sklearn
        score_pl = auroc(pred, target)  # Pytorch Lightning 
        assert torch.allclose(torch.tensor(score_pl).float(), torch.tensor(score_sk).float())