Releases
v1.5.3
New features
Improvments to ghost clipping
The interface for ghost clipping is now similar to that of PyTorch and vanilla DP-SGD (#668 )
Updated a tutorial on training language models with DP-SGD to include ghost clipping (#667 ) and LoRA (#698 )
Added adaptive clipping support for ghost clipping (#711 )
Add ghost clipping support for embedding layers (#694 )
Support generative NLP tasks with ghost clipping (#722 )
Add functionality to access per-sample gradients with ghost clipping (#724 )
Enabling more external contributions
Added a research folder for external contribution of promising new methods for PPML (#700 )
DP-SGD optimizers with Kalman filters are now available in the research folder (#706 )
Made it easier to define custom extensions of PrivacyEngine (#703 , #704 , #710 )
Bug fixes
Fix the clipping operation for ghost clipping when using the PrivacyEngine interface (#664 )
Fix issue with ghost clipping and BatchMemoryManager
Add strict
and force_functorch
parameters in initaliziation of GradSampleModuleFastGradientClipping
(#675 )
Fix failing tests (e.g., #726 , #713 , #727 , #674 )
Miscellaneous
Switch from testing with CircleCI to GithubActions CI (#701 )
Website and Github improvements (#723 , #721 , #677 , #712 )
Added multi-gpu test for ghost clipping (#665 )
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