About the hyper parameters for cifar and mnist

[carlini]

About the hyper parameters for cifar and mnist

[carlini]

The default parameters should work. I had someone else tell me earlier that the L0 attack wasn't performing correctly, but couldn't reproduce the issues to look into it.

Do you see this issue when running the code on your model? Or using the test script that's loaded here?

[lith0613]

The l0_attack was valid, but when I calculated L0 norm between the adversarial results and the original inputs, I found the L0 norm value was very big, very close to 3072 in cifar. Maybe these minor changes was caused during the save and reload process of float adv array. Thanks for your reply !

[carlini]

The save and load difference is possible. Could you check what the differences were between the images?

[lith0613]

The difference was caused by the data conversion process, I used my own data loading function and forgot to set the data type, the right action is as follows:

inputs = np.array(inputs,dtype='float32')