from torchmetrics.image import MultiScaleStructuralSimilarityIndexMeasure
import torch
preds = torch.rand([3, 3, 256, 256], generator=torch.manual_seed(42))
target = preds * 0.75
metric = MultiScaleStructuralSimilarityIndexMeasure(data_range=1.0)
values = [ ]
for _ in range(10):
    values.append(metric(preds, target))
fig_, ax_ = metric.plot(values)