restore fix

train.py

@@ -371,12 +371,18 @@ def main(args):
     if args.restore_path:
         checkpoint = torch.load(args.restore_path)
         model.load_state_dict(checkpoint['model'])
+        optimizer = optim.Adam(model.parameters(), lr=c.lr)
         optimizer.load_state_dict(checkpoint['optimizer'])
-        print("\n > Model restored from step %d\n" % checkpoint['step'])
+        for state in optimizer.state.values():
+            for k, v in state.items():
+                if torch.is_tensor(v):
+                    state[k] = v.cuda()
+        print(" > Model restored from step %d" % checkpoint['step'])
         start_epoch = checkpoint['step'] // len(train_loader)
         best_loss = checkpoint['linear_loss']
         start_epoch = 0
         args.restore_step = checkpoint['step']
+        optimizer_st = optim.Adam(model.decoder.stopnet.parameters(), lr=c.lr)
     else:
         args.restore_step = 0
         print("\n > Starting a new training")