-
Notifications
You must be signed in to change notification settings - Fork 2
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Refactor/feature layers id in fit #72
Conversation
by split_by_class
☂️ Python Coverage
Overall Coverage
New FilesNo new covered files... Modified Files
|
fix: fixed a test for torch FE chore: flake8
bd50602
to
5017714
Compare
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I don't know if you've already requested reviews, but this is my last contribution for the next 3 weeks 🏖️
Nice feature! It rocks 🚀
+ fix on mahalanobis
and some env req cleaning + added doc on plots. Also added viz on readme
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Good job! 💪
assign_ood_labels_by_class
withsplit_by_class
since it is more appropriate.feature_layers_id
argument in the method.fit
. It seems more natural since.fit
deals with the construction of theFeatureExtractor
, andOODBaseDetector.__init__()
with the parameters of the detector.requires_internal_features
toOODBaseDetector
to maintain the behavior where usage of detectors acting on internal features without specifying internal features would throw aValueError
. It was otherwise difficult because after PR score() returns information with predictions and labels #70feature_layers_id
is no longer used by methods that act on logits only so we cannot throw an error solely based on the criterion thatfeature_layers_id is None