code: def evaluate(self, brain_info):
          
          feed_dict = {self.model.dropout_rate: self.evaluate_rate,
                       self.model.sequence_length: 1}
  
          feed_dict = self._fill_eval_dict(feed_dict, brain_info)
          if self.use_recurrent:
              if brain_info.memories.shape[1] == 0:
                  brain_info.memories = self.make_empty_memory(len(brain_info.agents))
              feed_dict[self.model.memory_in] = brain_info.memories
          run_out = self._execute_model(feed_dict, self.inference_dict)
          return run_out
docs: Evaluates policy for the agent experiences provided.
          :param brain_info: BrainInfo input to network.
          :return: Results of evaluation.