Apply Black formatting

Signed-off-by: Beat Buesser <[email protected]>

Author: Beat Buesser

art/attacks/evasion/spatial_transformation.py

@@ -118,23 +118,11 @@ def generate(self, x: np.ndarray, y: Optional[np.ndarray] = None, **kwargs) -> n
 
             grid_trans_x = [
                 int(round(g))
-                for g in list(
-                    np.linspace(
-                        -max_num_pixel_trans_x,
-                        max_num_pixel_trans_x,
-                        num=self.num_translations,
-                    )
-                )
+                for g in list(np.linspace(-max_num_pixel_trans_x, max_num_pixel_trans_x, num=self.num_translations,))
             ]
             grid_trans_y = [
                 int(round(g))
-                for g in list(
-                    np.linspace(
-                        -max_num_pixel_trans_y,
-                        max_num_pixel_trans_y,
-                        num=self.num_translations,
-                    )
-                )
+                for g in list(np.linspace(-max_num_pixel_trans_y, max_num_pixel_trans_y, num=self.num_translations,))
             ]
             grid_rot = list(np.linspace(-self.max_rotation, self.max_rotation, num=self.num_rotations))
 
@@ -187,8 +175,7 @@ def generate(self, x: np.ndarray, y: Optional[np.ndarray] = None, **kwargs) -> n
             self.attack_rot = rot
 
             logger.info(
-                "Success rate of spatial transformation attack: %.2f%%",
-                100 * self.fooling_rate,
+                "Success rate of spatial transformation attack: %.2f%%", 100 * self.fooling_rate,
             )
             logger.info("Attack-translation in x: %.2f%%", self.attack_trans_x)
             logger.info("Attack-translation in y: %.2f%%", self.attack_trans_y)
@@ -211,10 +198,7 @@ def _perturb(self, x: np.ndarray, trans_x: int, trans_y: int, rot: float) -> np.
 
         if self.estimator.clip_values is not None:
             np.clip(
-                x_adv,
-                self.estimator.clip_values[0],
-                self.estimator.clip_values[1],
-                out=x_adv,
+                x_adv, self.estimator.clip_values[0], self.estimator.clip_values[1], out=x_adv,
             )
 
         return x_adv

art/attacks/extraction/copycat_cnn.py

@@ -62,7 +62,7 @@ def __init__(
         batch_size_query: int = 1,
         nb_epochs: int = 10,
         nb_stolen: int = 1,
-        use_probability: bool = False
+        use_probability: bool = False,
     ) -> None:
         """
         Create a Copycat CNN attack instance.