Notes

I see the issue now. It seems that the `state['question']` elements within `episode_states` are still lists and not tensors. You need to ensure that each element within `episode_states` is a tensor before concatenating them.

You can modify the code to convert the lists to tensors before concatenation. Here's how to do it:

```python
# Convert lists to tensors
question_tensors = [torch.tensor(state['question'], dtype=torch.float32) for state in episode_states]
correct_response_tensors = [torch.tensor(state['correct_response'], dtype=torch.float32) for state in episode_states]
incorrect_response_tensors = [torch.tensor(state['incorrect_response'], dtype=torch.float32) for state in episode_states]

# Concatenate the tensors
question_tensors = torch.cat(question_tensors)
correct_response_tensors = torch.cat(correct_response_tensors)
incorrect_response_tensors = torch.cat(incorrect_response_tensors)

# Forward pass through the policy network
action_probs = policy.forward(question_tensors, correct_response_tensors, incorrect_response_tensors)
```

This code should convert the lists of states into tensors before concatenation and then pass them to the `policy.forward` method.