update

1 files changed, 14 insertions, 16 deletions

diff --git a/models/cycle_gan_model.py b/models/cycle_gan_model.py
index e840e7b..fe06823 100644
--- a/models/cycle_gan_model.py
+++ b/models/cycle_gan_model.py
@@ -91,13 +91,13 @@ class CycleGANModel(BaseModel):
 
     def test(self):
         real_A = Variable(self.input_A, volatile=True)
-        fake_B = self.netG_A.forward(real_A)
-        self.rec_A = self.netG_B.forward(fake_B).data
+        fake_B = self.netG_A(real_A)
+        self.rec_A = self.netG_B(fake_B).data
         self.fake_B = fake_B.data
 
         real_B = Variable(self.input_B, volatile=True)
-        fake_A = self.netG_B.forward(real_B)
-        self.rec_B = self.netG_A.forward(fake_A).data
+        fake_A = self.netG_B(real_B)
+        self.rec_B = self.netG_A(fake_A).data
         self.fake_A = fake_A.data
 
     # get image paths
@@ -106,10 +106,10 @@ class CycleGANModel(BaseModel):
 
     def backward_D_basic(self, netD, real, fake):
         # Real
-        pred_real = netD.forward(real)
+        pred_real = netD(real)
         loss_D_real = self.criterionGAN(pred_real, True)
         # Fake
-        pred_fake = netD.forward(fake.detach())
+        pred_fake = netD(fake.detach())
         loss_D_fake = self.criterionGAN(pred_fake, False)
         # Combined loss
         loss_D = (loss_D_real + loss_D_fake) * 0.5
@@ -134,17 +134,16 @@ class CycleGANModel(BaseModel):
         # Identity loss
         if lambda_idt > 0:
             # G_A should be identity if real_B is fed.
-            idt_A = self.netG_A.forward(self.real_B)
+            idt_A = self.netG_A(self.real_B)
             loss_idt_A = self.criterionIdt(idt_A, self.real_B) * lambda_B * lambda_idt
             # G_B should be identity if real_A is fed.
-            idt_B = self.netG_B.forward(self.real_A)
+            idt_B = self.netG_B(self.real_A)
             loss_idt_B = self.criterionIdt(idt_B, self.real_A) * lambda_A * lambda_idt
 
             self.idt_A = idt_A.data
             self.idt_B = idt_B.data
             self.loss_idt_A = loss_idt_A.data[0]
             self.loss_idt_B = loss_idt_B.data[0]
-
         else:
             loss_idt_A = 0
             loss_idt_B = 0
@@ -152,23 +151,22 @@ class CycleGANModel(BaseModel):
             self.loss_idt_B = 0
 
         # GAN loss D_A(G_A(A))
-        fake_B = self.netG_A.forward(self.real_A)
-        pred_fake = self.netD_A.forward(fake_B)
+        fake_B = self.netG_A(self.real_A)
+        pred_fake = self.netD_A(fake_B)
         loss_G_A = self.criterionGAN(pred_fake, True)
 
         # GAN loss D_B(G_B(B))
-        fake_A = self.netG_B.forward(self.real_B)
-        pred_fake = self.netD_B.forward(fake_A)
+        fake_A = self.netG_B(self.real_B)
+        pred_fake = self.netD_B(fake_A)
         loss_G_B = self.criterionGAN(pred_fake, True)
 
         # Forward cycle loss
-        rec_A = self.netG_B.forward(fake_B)
+        rec_A = self.netG_B(fake_B)
         loss_cycle_A = self.criterionCycle(rec_A, self.real_A) * lambda_A
 
         # Backward cycle loss
-        rec_B = self.netG_A.forward(fake_A)
+        rec_B = self.netG_A(fake_A)
         loss_cycle_B = self.criterionCycle(rec_B, self.real_B) * lambda_B
-
         # combined loss
         loss_G = loss_G_A + loss_G_B + loss_cycle_A + loss_cycle_B + loss_idt_A + loss_idt_B
         loss_G.backward()