[DRAFT] FEAT Add adversarial suffix attack GCG

[NaijingGuo]

Description

suffix attack from https://arxiv.org/pdf/2307.15043.pdf
TODO:

• support llama3 and Phi-3
• test and add in the script for multiple prompt multiple models
• add the option to specify what token is not allowed as suffix
• [add suffix examples suffix converter] (need approval)

Tests and Documentation

Tests and documentation to be added.

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[romanlutz]

Instead of a "main" script, let's have a class, e.g., GreedyCoordinateGradientAdversarialSuffixGenerator (wow that's long...) that takes the parameters as inputs and has a method generate_suffix. We can call it from a notebook (I would put it under doc/demo/7_adversarial_suffix (the number may change but that's fine).

[NaijingGuo]

I have changed the code to put things in a class as suggested, generate_suffix under the class can be called from outside. The change can be seen in 2 files, named test_main.py (contains the class) and test_demo.py (contains example usage of the class).

However, because the original code uses multiprocessing, if __name__ == "__main__" guard is required to run the code, and this would also introduces difficulty running in Jupyter notebook (although I have been using python scripts only, since the school cluster does not support notebook). My main reference is here:

• Torch.multiprocessing pool hangs in Jupyter notebooks pytorch/pytorch#17680
• https://stackoverflow.com/questions/20360686/compulsory-usage-of-if-name-main-in-windows-while-using-multiprocessi

In other words, in my test_demo.py, I cannot remove if __name__ == "__main__ and run generate_suffix directly. I have not found a way to circumvent this yet (but I'm completely new to multiprocessing, there might be ways that I have not dug up yet somewhere in Stack Overflow...)

I was wondering if if __name__ == "__main__" guard is a huge problem and we should stop using multiprocessing altogether, or we can keep the demo like test_demo.py for now, or there are some ways that you know that can help circumvent this problem.

[romanlutz]

Don't worry about notebooks. I expect this code will always be executed on a compute node of some kind using a little script that has the main guard BUT the logic should be only in the code files if that makes sense. For example, we have all our logic in the pyrit package today and can call it in a notebook. But we could just as well use a little python script to call it without a notebook. The notebook is just one way.

Do you have a recommendation on how to run it? I can try if it works

[NaijingGuo]

Yes, the test_demo.py file would be the little script to run suffix generation (I can run it without any problem, but please let me know if it doesn't work for you). The main logic is in the test_main.py, and test_demo.py only specifies model name and training parameters, like training steps, batch size, etc..

(The two files were called test_xxx because they are my draft to refactor the original main and the bash script to run main. I have not deleted the original code yet.)

[romanlutz]

Let's try to put everything in classes & functions, and call them from notebooks under doc

[NaijingGuo]

I have refactored the parse_scirpt.py and the evaluation into a class called AdversarialSuffixEvaluator (this class in the new test_evaluation.py. And an example to run the evaluation can be found in the new test_eval_demo.py.

If the evaluator and generator class both looks good, I will combine the demo code files such that it can run both generation and evaluation.

[romanlutz]

Not urgent, but eventually we'd want to use the logger the same way we do elsewhere in the repo. That way, you can specify the desired log level and only see the corresponding output.

[romanlutz]

FYI #192 (comment)