code: def decode(self, output_dict: Dict[str, torch.Tensor]) -> Dict[str, torch.Tensor]:
          
          action_mapping = output_dict['action_mapping']
          best_actions = output_dict["best_action_sequence"]
          debug_infos = output_dict['debug_info']
          batch_action_info = []
          for batch_index, (predicted_actions, debug_info) in enumerate(zip(best_actions, debug_infos)):
              instance_action_info = []
              for predicted_action, action_debug_info in zip(predicted_actions, debug_info):
                  action_info = {}
                  action_info['predicted_action'] = predicted_action
                  considered_actions = action_debug_info['considered_actions']
                  probabilities = action_debug_info['probabilities']
                  actions = []
                  for action, probability in zip(considered_actions, probabilities):
                      if action != -1:
                          actions.append((action_mapping[(batch_index, action)], probability))
                  actions.sort()
                  considered_actions, probabilities = zip(*actions)
                  action_info['considered_actions'] = considered_actions
                  action_info['action_probabilities'] = probabilities
                  action_info['question_attention'] = action_debug_info.get('question_attention', [])
                  instance_action_info.append(action_info)
              batch_action_info.append(instance_action_info)
          output_dict["predicted_actions"] = batch_action_info
          return output_dict
docs: This method overrides ``Model.decode``, which gets called after ``Model.forward``, at test
          time, to finalize predictions.  This is (confusingly) a separate notion from the "decoder"
          in "encoder/decoder", where that decoder logic lives in the ``TransitionFunction``.
  
          This method trims the output predictions to the first end symbol, replaces indices with
          corresponding tokens, and adds a field called ``predicted_tokens`` to the ``output_dict``.