Rename attack runner helper

src/torchattack/admix.py

@@ -131,6 +131,6 @@ def x_admix(x: torch.Tensor) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(Admix, {'eps': 8 / 255, 'steps': 10})

src/torchattack/deepfool.py

@@ -176,6 +176,6 @@ def _atleast_kd(self, x: torch.Tensor, k: int) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(DeepFool, attack_cfg={'steps': 50, 'overshoot': 0.02}, model='resnet152')

src/torchattack/difgsm.py

@@ -162,7 +162,7 @@ def input_diversity(
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     cfgs = {'eps': 16 / 255, 'steps': 10, 'resize_rate': 0.9, 'diversity_prob': 1.0}
     run_attack(DIFGSM, attack_cfg=cfgs)

src/torchattack/fgsm.py

@@ -78,6 +78,6 @@ def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(FGSM, {'eps': 8 / 255, 'clip_min': 0.0, 'clip_max': 1.0})

src/torchattack/fia.py

@@ -163,6 +163,6 @@ def __backward_hook(self, m: nn.Module, i: torch.Tensor, o: torch.Tensor):
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(FIA, {'eps': 8 / 255, 'steps': 10, 'feature_layer': 'layer2'})

src/torchattack/geoda.py

@@ -365,6 +365,6 @@ def is_adv(self, x_adv: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(GeoDA, {'epsilon': 4, 'p': 'l2', 'max_queries': 4000}, batch_size=2)

src/torchattack/mifgsm.py

@@ -101,6 +101,6 @@ def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(MIFGSM, {'eps': 8 / 255, 'steps': 10})

src/torchattack/nifgsm.py

@@ -109,6 +109,6 @@ def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(NIFGSM, {'eps': 8 / 255, 'steps': 10})

src/torchattack/pgd.py

@@ -104,6 +104,6 @@ def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(PGD, {'eps': 8 / 255, 'steps': 20, 'random_start': True})

src/torchattack/pgdl2.py

@@ -119,6 +119,6 @@ def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(PGDL2, {'eps': 1.0, 'steps': 10, 'random_start': False})

src/torchattack/utils.py → src/torchattack/runner.py

@@ -1,4 +1,18 @@
-def run_attack(attack, attack_cfg, model='resnet50', samples=100, batch_size=8) -> None:
+from contextlib import suppress
+
+import torch
+import torchvision as tv
+
+from torchattack.dataset import NIPSLoader
+
+
+def run_attack(
+    attack,
+    attack_cfg,
+    model: str = 'resnet50',
+    samples: int = 100,
+    batch_size: int = 8,
+) -> None:
     """Helper function to run attacks in `__main__`.
 
     Example:
@@ -10,17 +24,10 @@ def run_attack(attack, attack_cfg, model='resnet50', samples=100, batch_size=8)
     Args:
         attack: The attack class to initialize.
         attack_cfg: A dict of keyword arguments passed to the attack class.
-        model: The model to attack. Defaults to "resnet50".
+        model: The torchvision model to attack. Defaults to "resnet50".
         samples: Max number of samples to attack. Defaults to 100.
     """
 
-    from contextlib import suppress
-
-    import torch
-    import torchvision as tv
-
-    from torchattack.dataset import NIPSLoader
-
     # Try to import rich for progress bar
     with suppress(ImportError):
         from rich import print

src/torchattack/sinifgsm.py

@@ -121,6 +121,6 @@ def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(SINIFGSM, {'eps': 8 / 255, 'steps': 10, 'm': 3})

src/torchattack/tifgsm.py

@@ -141,6 +141,6 @@ def gkern(kern_len: int = 15, n_sig: int = 3) -> np.ndarray:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(TIFGSM, {'eps': 8 / 255, 'steps': 10, 'kern_len': 15, 'n_sig': 3})

src/torchattack/vmifgsm.py

@@ -136,6 +136,6 @@ def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(VMIFGSM, {'eps': 8 / 255, 'steps': 10, 'n': 5, 'beta': 1.5})

src/torchattack/vnifgsm.py

@@ -139,6 +139,6 @@ def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
 
 
 if __name__ == '__main__':
-    from torchattack.utils import run_attack
+    from torchattack.runner import run_attack
 
     run_attack(VNIFGSM, {'eps': 8 / 255, 'steps': 10, 'n': 5, 'beta': 1.5})