v0.2.0

• New baseline: Gram! Detecting Out-of-Distribution Examples with Gram Matrices, ICML 2020. Check out the tutorial to know more :).
• FeatureExtractor.predict() and FeatureExtractor.predict_tensor() now takes a new argument as input: postproc_fns. This argument is a list of Callable functions that applies to the batch features obtained after each (batch-wise) forward. It allows us to perform postprocessing on internal features on the fly rather than after a forward pass on the whole dataset that would require saving the features of the whole dataset in GPU memory, likely leading to an OOM (especially for feature maps).

v0.1.1

Hotfix for v0.1.0

==========

First Release on Pypi!
Check out the doc and Readme to get to know oodeel!

This release is stable, but still beta since although usable and self-contained, it does not encompass all the end-goal features that we plan to implement.

v0.1.0

First Release on Pypi!
Check out the doc and Readme to get to know oodeel!

This release is stable, but still beta since although usable and self-contained, it does not encompass all the end-goal features that we plan to implement.