fix typo

models/OpenEdit_model.py

@@ -25,7 +25,6 @@ def __init__(self, opt):
 
         self.generator = opt.netG
 
-        self.noise_range = opt.noise_range
         if self.perturbation:
             self.netP = PerturbationNet(opt)
             self.netP.cuda()

trainers/OpenEdit_trainer.py

@@ -40,3 +40,35 @@ def run_discriminator_one_step(self, data):
         d_loss.backward()
         self.optimizer_D.step()
         self.d_losses = d_losses
+
+    def get_latest_losses(self):
+        return {**self.g_losses, **self.d_losses}
+
+    def get_latest_generated(self):
+        return self.generated
+
+    def save(self, epoch):
+        self.open_edit_model_on_one_gpu.save(epoch)
+
+    def update_learning_rate(self, epoch):
+        if epoch > self.opt.niter:
+            lrd = self.opt.lr / self.opt.niter_decay
+            new_lr = self.old_lr - lrd
+        else:
+            new_lr = self.old_lr
+
+        if new_lr != self.old_lr:
+            if self.opt.no_TTUR:
+                new_lr_G = new_lr
+                new_lr_D = new_lr
+            else:
+                new_lr_G = new_lr / 2
+                new_lr_D = new_lr * 2
+
+            if self.loss_gan:
+                for param_group in self.optimizer_D.param_groups:
+                    param_group['lr'] = new_lr_D
+            for param_group in self.optimizer_G.param_groups:
+                param_group['lr'] = new_lr_G
+            print('update learning rate: %f -> %f' % (self.old_lr, new_lr))
+            self.old_lr = new_lr