Comments (2)
- I am sorry to say that, for the all-to-all attack, we only have done the basic implementation early in the bd_attack_generate.py file. We haven't done a comprehensive compatibility test for every attack method. So you may meet a problem with some attack methods.
- I tried your setting in the blended attack. What I have done is replace the corresponding hyper-parameters in the YAML file. But I do not meet your problem. And I see that in your traceback information, it shows you are using the "./attack/laser_attack.py" script, so I am not sure how the problem comes. If you can offer more about your script, I can help you more.
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I run 'all-to-all' settings by commenting out 'attack_target'.
I'm sorry I disturbed you. 😣
amp: False
device: cuda:0
attack_label_trans: all2all
# attack_target: 0
attack_label_shift_amount: 1
num_classses: 10
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Related Issues (20)
- v2.0 run scripts
- Results for Tiny Imagenet HOT 1
- A data loading problem of LC attack HOT 2
- fine-pruning is missing HOT 1
- Bugs in WaNet All2All Attack HOT 1
- the data of leaderboard(asr of blended to nad) HOT 2
- Attack my own datasets made with videos. HOT 1
- Errors when we execute shell script
- LC attack source HOT 1
- missing resource
- Cannot generate poison data in SSBA algorithm HOT 5
- can not generate trigger for low frequency attack HOT 2
- Target Class of Label-Consistent in the Google Drive
- 您好,很敬佩该工作对于后门攻击的总结。 想请问下为什么 v1 里的 ft_attack 频域后门攻击 在v2 里被移除了呢
- How to use this library in an incremental manner? HOT 1
- Implementation issue with ANP HOT 3
- Poison Index Selection - Clean label case HOT 3
- bpp attack source HOT 2
- Backdoor OneDrive Access Unavailable HOT 5
- About Missing Clean Model for TrojanNN Attack Implementation HOT 2
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