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