diff --git a/codes/models/SRGAN_model.py b/codes/models/SRGAN_model.py
index 7e4fd2e7..fa330a09 100644
--- a/codes/models/SRGAN_model.py
+++ b/codes/models/SRGAN_model.py
@@ -89,6 +89,7 @@ class SRGANModel(BaseModel):
             # D_update_ratio and D_init_iters
             self.D_update_ratio = train_opt['D_update_ratio'] if train_opt['D_update_ratio'] else 1
             self.D_init_iters = train_opt['D_init_iters'] if train_opt['D_init_iters'] else 0
+            self.G_warmup = train_opt['G_warmup'] if train_opt['G_warmup'] else 0
             self.D_noise_theta = train_opt['D_noise_theta_init'] if train_opt['D_noise_theta_init'] else 0
             self.D_noise_final = train_opt['D_noise_final_it'] if train_opt['D_noise_final_it'] else 0
             self.D_noise_theta_floor = train_opt['D_noise_theta_floor'] if train_opt['D_noise_theta_floor'] else 0
@@ -300,7 +301,7 @@ class SRGANModel(BaseModel):
             _t = time()
 
         # D
-        if self.l_gan_w > 0:
+        if self.l_gan_w > 0 and step > self.G_warmup:
             for p in self.netD.parameters():
                 p.requires_grad = True
 
@@ -413,7 +414,7 @@ class SRGANModel(BaseModel):
             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)
-        if self.l_gan_w > 0:
+        if self.l_gan_w > 0 and step > self.G_warmup:
             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()))