For binary classification, AUROC metric requires a proba just of the class 1, with shape of (N,) rather then (N,C) as for multiclass.
https://lightning.ai/docs/torchmetrics/stable/classification/auroc.html#binaryauroc
So, right now binary classification AUROCmetric should fail (at least, it always fails for me). We may check why CI tests work as expected btw...
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~[ ] Function/class source code documentation added/updated (ensure typing is used to provide type hints, including and not limited to using Optional if a variable has a pre-defined value).~
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[ ] Tests added or modified to cover the changes; if coverage is reduced, please give explanation.
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For binary classification, AUROC metric requires a proba just of the class 1, with shape of
(N,)
rather then(N,C)
as for multiclass. https://lightning.ai/docs/torchmetrics/stable/classification/auroc.html#binaryauroc So, right now binary classification AUROCmetric should fail (at least, it always fails for me). We may check why CI tests work as expected btw...Checklist
CONTRIBUTING
guide has been followed.typing
is used to provide type hints, including and not limited to usingOptional
if a variable has a pre-defined value).~pip install
step is needed for PR to be functional), please ensure it is reflected in all the files that control the CI, namely: python-test.yml, and all docker files [1,2,3].~