@@ -78,8 +78,6 @@ class TestModel(BaseModel):
        black = np.zeros((1, 3, image.size(2), image.size(3)))
        black = torch.FloatTensor(black).cuda()
        input_adv, perturb = pgd_attack.perturb(image, black)      
-
-        black = None
        
        return input_adv, perturb

@@ -94,9 +92,6 @@ class TestModel(BaseModel):
        l2 = F.mse_loss(generated, generated_noattack)
        l0 = (generated - generated_noattack).norm(0)
        d = (generated - generated_noattack).norm(float('-inf'))
-
-        generated = None
-        generated_noattack = None
        
        return l1, l2, l0, d

@@ -85,13 +85,6 @@ if __name__ == '__main__':
            print('processing (%04d)-th image... %s' % (i, img_path))
        save_images(webpage, visuals, img_path, aspect_ratio=opt.aspect_ratio, width=opt.display_winsize)

-        model.fake = None
-        model.real = None
-        model.fake_noattack = None
-        data = None
-        perturb = None
-        input_adv = None
-
    webpage.save()  # save the HTML


@@ -35,10 +35,8 @@ class LinfPGDAttack(object):

            eta = torch.clamp(X_adv - X_nat, min=-self.epsilon, max=self.epsilon)
            X = torch.clamp(X_nat + eta, min=-1, max=1).detach_()
-            eta = None
-            X_adv = None

-        return X, X - X_nat
+        return X, eta

 def clip_tensor(X, Y, Z):
    # Clip X with Y min and Z max