diff --git a/codes/models/SRGAN_model.py b/codes/models/SRGAN_model.py
index 19665e67..fa1dea4d 100644
--- a/codes/models/SRGAN_model.py
+++ b/codes/models/SRGAN_model.py
@@ -347,13 +347,15 @@ class SRGANModel(BaseModel):
             if self.cri_fea:
                 self.add_log_entry('feature_weight', self.l_fea_w)
                 self.add_log_entry('l_g_fea', l_g_fea.item())
-            self.add_log_entry('l_g_gan', l_g_gan.item())
+            if self.l_gan_w > 0:
+                self.add_log_entry('l_g_gan', l_g_gan.item())
             self.add_log_entry('l_g_total', l_g_total.item() * self.mega_batch_factor)
-        self.add_log_entry('l_d_real', l_d_real.item() * self.mega_batch_factor)
-        self.add_log_entry('l_d_fake', l_d_fake.item() * self.mega_batch_factor)
-        self.add_log_entry('D_fake', torch.mean(pred_d_fake.detach()))
-        self.add_log_entry('D_diff', torch.mean(pred_d_fake) - torch.mean(pred_d_real))
-        self.add_log_entry('noise_theta', noise_theta)
+        if self.l_gan_w > 0:
+            self.add_log_entry('l_d_real', l_d_real.item() * self.mega_batch_factor)
+            self.add_log_entry('l_d_fake', l_d_fake.item() * self.mega_batch_factor)
+            self.add_log_entry('D_fake', torch.mean(pred_d_fake.detach()))
+            self.add_log_entry('D_diff', torch.mean(pred_d_fake) - torch.mean(pred_d_real))
+            self.add_log_entry('noise_theta', noise_theta)
 
         if step % self.corruptor_swapout_steps == 0 and step > 0:
             self.load_random_corruptor()