)) >>> fig_, ax_ = metric.plot(metric.compute()) .. plot:: :scale: 75 >>> # Example plotting multiple values >>> import torch >>> from torchmetrics.clustering import AdjustedRandScore >>> metric = AdjustedRandScore() >>> values = [ ] >>> for _ in range(10): ... values.append(metric(torch.randint(0, 4, (10,)), torch.randint(0, 4, (10,)))) >>> fig_, ax_ = metric.plot(values) )