import torch
from torchmetrics.classification import MultilabelAUROC
metric = MultilabelAUROC(num_labels=3)
values = [ ]
for _ in range(10):
    values.append(metric(torch.rand(20,3), torch.randint(2, (20,3))))
fig_, ax_ = metric.plot(values)