Add Fast Minimum-Norm Attack (FMN)#165
Conversation
- Add documentation - Add support functions
- Update forward function
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #165 +/- ##
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- Coverage 73.37% 72.74% -0.63%
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Files 44 45 +1
Lines 3827 3985 +158
Branches 578 590 +12
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+ Hits 2808 2899 +91
- Misses 862 925 +63
- Partials 157 161 +4
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Hello @rikonaka, thank you for maintaining this library. Do you have any update on this PR? Is there something that we can do to speed up the merge? |
Well, all we can do now is wait 🤣. But if you have other urgent reasons for the merge, you can send an email to Harry and ask him to help merge it. As far as I know, this process may takes about 3 to 6 months. In the meantime, you can continue to check and patch the code 😁. |
Good, we will wait. Thank you ;) |
PR Type and Checklist
What kind of change does this PR introduce?
model.supported_modewhether the attack supports targeted mode.Fast Minimum-Norm Attack Info
Fast Minimum-Norm Attack PyTorch implementation; works with PyTorch optimizers and schedulers and supports default and targeted mode, with L0, L1, L2 and Linf norms.
Original Code
Paper
Citation.