chatbot_tutorial.py: Solve the optimizer cuda call problem

If you don't configure this string of code, you will get an error when you iterate over the update from 4000_checkpoint.tar:

```
encoder_optimizer.step()  
```

Error message:

```
exp_avg.mul_(beta1).add_(1 - beta1, grad)
RuntimeError: expected backend CPU and dtype Float but got backend CUDA and dtype Float
```

Fix it: pytorch/pytorch#2830

```
model = Model()
model.load_state_dict(checkpoint['model'])
model.cuda()
optimizer = optim.Adam(model.parameters())
optimizer.load_state_dict(checkpoint['optimizer'])
for state in optimizer.state.values():
    for k, v in state.items():
        if isinstance(v, torch.Tensor):
            state[k] = v.cuda()
```

Author: jiangzhonglian

beginner_source/chatbot_tutorial.py

@@ -1326,6 +1326,10 @@ def evaluateInput(encoder, decoder, searcher, voc):
 print('Building optimizers ...')
 encoder_optimizer = optim.Adam(encoder.parameters(), lr=learning_rate)
 decoder_optimizer = optim.Adam(decoder.parameters(), lr=learning_rate * decoder_learning_ratio)
+if loadFilename:
+    encoder_optimizer.load_state_dict(encoder_optimizer_sd)
+    decoder_optimizer.load_state_dict(decoder_optimizer_sd)
+
 # If you have cuda, configure cuda to call
 for state in encoder_optimizer.state.values():
     for k, v in state.items():
@@ -1336,11 +1340,7 @@ def evaluateInput(encoder, decoder, searcher, voc):
     for k, v in state.items():
         if isinstance(v, torch.Tensor):
             state[k] = v.cuda()
-
-if loadFilename:
-    encoder_optimizer.load_state_dict(encoder_optimizer_sd)
-    decoder_optimizer.load_state_dict(decoder_optimizer_sd)
-
+    
 # Run training iterations
 print("Starting Training!")
 trainIters(model_name, voc, pairs, encoder, decoder, encoder_optimizer, decoder_optimizer,