Active Learning Refactoring and Minor Improvements
Active Learning Refactoring and Minor Improvements
Instantiate shuffle tensor directly on device
This change makes our momentum encoders more efficient by directly instantiating temporary tensors on device instead of moving them there after instantiation. Thanks a lot to @guarin for pointing out the problem and swiftly fixing it!
Active Learning Refactoring
The new strategy of uploading active learning scores to a query tag instead of the preselected tag is enforced making our framework more flexible, easier to use, and allowing users to make several samplings with the same set of scores at the cost of little computational overhead.
Additionally, active learning scores were renamed to match the current literature. We now support uncertainty sampling with the least confidence, margin and entropy variant as described in http://burrsettles.com/pub/settles.activelearning.pdf, page 12f, chapter 3.1.
Minor Bug Fixes and Improvements
Better handling of edge cases when doing active learning for object detection.