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