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Description
🐛 Bug
AUROC calculation is different when being called differently.
To Reproduce
Copy the following code and run.
Note that when .update() is called, values that are greater than 1.0 will be scaled using the sigmoid activation, values that is less than 1.0 will not be scaled. This result in the compute step to compute with the wrong input values. However, directly calling the auroc will not rescale the value
from torchmetrics import AUROC
from torch import tensor
pp = tensor([tensor([1.2]), tensor([0.9678]), tensor([1.7])])
tt = tensor([tensor([1]), tensor([0]), tensor([1])])
auroc = AUROC(num_classes=1, task="binary")
print("Forward:", auroc(pp, tt))
for p, t in zip(pp, tt):
auroc.update(p, t)
print(auroc.preds, auroc.target)
print("Update and Compute:", auroc.compute())
Expected behavior
The reported AUROC metrics for both cases should be the same.
Environment
- TorchMetrics 1.0.3
- Python 3.9.16
- PyTorch 1.13.1