Madry Challenge C&W attack (name scopes)

[Yash Sharma]

Can the Cleverhans wrapper for the Madry challenge be used with the C&W attack? The C&W attack uses tf variables, so the fact that the Madry model can't be put in a scope means that when running saver.restore, the saver will also attempt to restore the variables in the C&W attack. 

Is there any way around this? I understand why the Madry model can't be wrapped in a scope, but given that, I don't know how to make sure the C&W attack variables aren't restored.

I don't think this issue is unique to Cleverhans, but is an issue with the Madry challenge in general. Any ideas?

[Nicholas Carlini]

This is one of those things that tensorflow makes difficult,
with the save/restore functionality. You can handle this by
selectively restoring variables by passing those in to the
constructor. Maybe someone can put together a PR that
does this for the challenge to only restore the variables
used in the model.


Nicholas

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[Ian Goodfellow]

If anyone wants to work on this, let me know and I'll send you
Fartash's code from the Google repo

On Mon, Oct 9, 2017 at 1:35 PM, Fartash Faghri <fartash...@gmail.com> wrote:
> Hi Ian,
>
> I had a code which I pushed to g3 experimental but not github that solves
> this issue. The file load_madry.py in three_softmax/ simply assigns values
> only to the tensors of Madry's model. If someone wanted to make a PR, they
> can start from that code.
>
> Fartash

>> https://groups.google.com/d/msgid/cleverhans-dev/3FE6A176-F962-4622-A906-07B62FC3F21C%40gmail.com.

[Angus Galloway]

I have been using the WideResNet from the Madry CIFAR-10 challenge with the CleverHans model class and so far all attacks work fine e.g., PGD, CWL2 and do not interfere with loading the pre-trained public/secret checkpoints. My current implementation is here: https://github.com/uoguelph-mlrg/adversarial_training_vs_weight_decay/blob/master/cifar10/MadryLab/cleverhans_model.py 

I'm willing to tidy this up and submit a PR if there's interest, but would require some input as to how this fits within the existing framework, without creating another tutorial to maintain. I think this would be a nice complement to the vanilla CNN and accelerate the community's understanding of the limitations of the "PGD + high capacity" defense. The original code is quite slow as perturbations are computed on the CPU with numpy and is geared toward black-box attack submissions.

[Nicolas Papernot]

This sounds like it would be a great addition to the examples folder. There is already a folder there that wraps the challenge code to the CleverHans model, but you may have code that can help improve it.

On Tue, May 15, 2018, 11:54 AM Angus Galloway <premiumd...@gmail.com> wrote:

I have been using the WideResNet from the Madry CIFAR-10 challenge with the CleverHans model class and so far all attacks work fine e.g., PGD, CWL2 and do not interfere with loading the pre-trained public/secret checkpoints. My current implementation is here: https://github.com/uoguelph-mlrg/adversarial_training_vs_weight_decay/blob/master/cifar10/MadryLab/cleverhans_model.py 

I'm willing to tidy this up and submit a PR if there's interest, but would require some input as to how this fits within the existing framework, without creating another tutorial to maintain. I think this would be a nice complement to the vanilla CNN and accelerate the community's understanding of the limitations of the "PGD + high capacity" defense. The original code is quite slow as perturbations are computed on the CPU with numpy and is geared toward black-box attack submissions.

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