import torch
from torchmetrics.image import UniversalImageQualityIndex
preds = torch.rand([16, 1, 16, 16])
target = preds * 0.75
metric = UniversalImageQualityIndex()
values = [ ]
for _ in range(10):
    values.append(metric(preds, target))
fig_, ax_ = metric.plot(values)