next

cyclegan/models/test_model.py

@@ -91,32 +91,6 @@ class TestModel(BaseModel):
         d = (generated - generated_noattack).norm(float('-inf'))
         return l1, l2, l0, d
 
-    def attack(self, label, inst, image=None):
-        # Encode Inputs        
-        image = Variable(image) if image is not None else None
-        input_label, inst_map, real_image, _ = self.encode_input(Variable(label), Variable(inst), image, infer=True)
-
-        # Fake Generation
-        if self.use_features:
-            if self.opt.use_encoded_image:
-                # encode the real image to get feature map
-                feat_map = self.netE.forward(real_image, inst_map)
-            else:
-                # sample clusters from precomputed features             
-                feat_map = self.sample_features(inst_map)
-            input_concat = torch.cat((input_label, feat_map), dim=1)                        
-        else:
-            input_concat = input_label  
-
-        # Attack
-        pgd_attack = attacks.LinfPGDAttack(model=self.netG)
-        black = np.zeros((1, 3, input_concat.size(2), input_concat.size(3)))
-        black = torch.FloatTensor(black).cuda()
-        # print(input_concat.size())
-        input_adv, perturb = pgd_attack.perturb(input_concat, black)      
-        
-        return input_adv, perturb
-
     def optimize_parameters(self):
         """No optimization for test model."""
         pass