| import time |
|
|
| from ..attack import Attack |
| from ..wrappers.multiattack import MultiAttack |
| from .apgd import APGD |
| from .apgdt import APGDT |
| from .fab import FAB |
| from .square import Square |
|
|
|
|
| class AutoAttack(Attack): |
| r""" |
| AutoAttack in the paper 'Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks' |
| [https://arxiv.org/abs/2003.01690] |
| [https://github.com/fra31/auto-attack] |
| |
| Distance Measure : Linf, L2 |
| |
| Arguments: |
| model (nn.Module): model to attack. |
| norm (str) : Lp-norm to minimize. ['Linf', 'L2'] (Default: 'Linf') |
| eps (float): maximum perturbation. (Default: 0.3) |
| version (bool): version. ['standard', 'plus', 'rand'] (Default: 'standard') |
| n_classes (int): number of classes. (Default: 10) |
| seed (int): random seed for the starting point. (Default: 0) |
| verbose (bool): print progress. (Default: False) |
| |
| Shape: |
| - images: :math:`(N, C, H, W)` where `N = number of batches`, `C = number of channels`, `H = height` and `W = width`. It must have a range [0, 1]. |
| - labels: :math:`(N)` where each value :math:`y_i` is :math:`0 \leq y_i \leq` `number of labels`. |
| - output: :math:`(N, C, H, W)`. |
| |
| Examples:: |
| >>> attack = torchattacks.AutoAttack(model, norm='Linf', eps=8/255, version='standard', n_classes=10, seed=None, verbose=False) |
| >>> adv_images = attack(images, labels) |
| |
| """ |
|
|
| def __init__( |
| self, |
| model, |
| norm="Linf", |
| eps=8 / 255, |
| version="standard", |
| n_classes=10, |
| seed=None, |
| verbose=False, |
| ): |
| super().__init__("AutoAttack", model) |
| self.norm = norm |
| self.eps = eps |
| self.version = version |
| self.n_classes = n_classes |
| self.seed = seed |
| self.verbose = verbose |
| self.supported_mode = ["default"] |
|
|
| if version == "standard": |
| self._autoattack = MultiAttack( |
| [ |
| APGD( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| loss="ce", |
| n_restarts=1, |
| ), |
| APGDT( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| n_classes=n_classes, |
| n_restarts=1, |
| ), |
| FAB( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| multi_targeted=True, |
| n_classes=n_classes, |
| n_restarts=1, |
| ), |
| Square( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| n_queries=5000, |
| n_restarts=1, |
| ), |
| ] |
| ) |
|
|
| |
| elif version == "plus": |
| self._autoattack = MultiAttack( |
| [ |
| APGD( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| loss="ce", |
| n_restarts=5, |
| ), |
| APGD( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| loss="dlr", |
| n_restarts=5, |
| ), |
| FAB( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| n_classes=n_classes, |
| n_restarts=5, |
| ), |
| Square( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| n_queries=5000, |
| n_restarts=1, |
| ), |
| APGDT( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| n_classes=n_classes, |
| n_restarts=1, |
| ), |
| FAB( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| multi_targeted=True, |
| n_classes=n_classes, |
| n_restarts=1, |
| ), |
| ] |
| ) |
|
|
| elif version == "rand": |
| self._autoattack = MultiAttack( |
| [ |
| APGD( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| loss="ce", |
| eot_iter=20, |
| n_restarts=1, |
| ), |
| APGD( |
| model, |
| eps=eps, |
| norm=norm, |
| seed=self.get_seed(), |
| verbose=verbose, |
| loss="dlr", |
| eot_iter=20, |
| n_restarts=1, |
| ), |
| ] |
| ) |
|
|
| else: |
| raise ValueError("Not valid version. ['standard', 'plus', 'rand']") |
|
|
| def forward(self, images, labels): |
| r""" |
| Overridden. |
| """ |
|
|
| images = images.clone().detach().to(self.device) |
| labels = labels.clone().detach().to(self.device) |
| adv_images = self._autoattack(images, labels) |
|
|
| return adv_images |
|
|
| def get_seed(self): |
| return time.time() if self.seed is None else self.seed |
|
|
