-
Notifications
You must be signed in to change notification settings - Fork 1.2k
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
TRADES adversarial training protocol #2131
Conversation
Codecov Report
❗ Your organization is not using the GitHub App Integration. As a result you may experience degraded service beginning May 15th. Please install the Github App Integration for your organization. Read more. @@ Coverage Diff @@
## dev_1.15.0 #2131 +/- ##
===============================================
+ Coverage 73.39% 85.63% +12.24%
===============================================
Files 297 299 +2
Lines 26521 26648 +127
Branches 4864 4878 +14
===============================================
+ Hits 19464 22821 +3357
+ Misses 5930 2580 -3350
- Partials 1127 1247 +120
|
Signed-off-by: Muhammad Zaid Hameed <Zaid.Hameed@ibm.com>
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.
Hi @Zaid-Hameed Thank you very much for your pull request! I have a few minor review comments, what do you think?
Signed-off-by: Muhammad Zaid Hameed <Zaid.Hameed@ibm.com>
Signed-off-by: Muhammad Zaid Hameed <Zaid.Hameed@ibm.com>
raise NotImplementedError | ||
|
||
@abc.abstractmethod | ||
def fit_generator(self, generator: DataGenerator, nb_epochs: int = 20, **kwargs): |
Check notice
Code scanning / CodeQL
Mismatch between signature and use of an overridden method
Signed-off-by: Muhammad Zaid Hameed <Zaid.Hameed@ibm.com>
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.
Hi @Zaid-Hameed Thank you very much and congratulations to your first PR merged to ART!
Thanks a lot @beat-buesser for all the help in it and the review. :) |
Description
TRADES is an important adversarial training approach because it provides a better tradeoff between robustness against adversarial attacks and clean accuracy. TRADES has been proposed in paper "Theoretically Principled Trade-off between Robustness and Accuracy".
Paper link: https://proceedings.mlr.press/v97/zhang19p.html
It is also standard component of recent and more advanced adversarial training approaches.
Fixes #2031
Type of change
Please check all relevant options.
Testing
Please describe the tests that you ran to verify your changes. Consider listing any relevant details of your test configuration.
Test Configuration:
Checklist