@timed
def evaluate(self, brain_info):
    '\n        Evaluates policy for the agent experiences provided.\n        :param brain_info: BrainInfo object containing inputs.\n        :return: Outputs from network as defined by self.inference_dict.\n        '
    feed_dict = {self.model.batch_size: len(brain_info.vector_observations), self.model.sequence_length: 1}
    epsilon = None
    if self.use_recurrent:
        if (not self.use_continuous_act):
            feed_dict[self.model.prev_action] = self.retrieve_previous_action(brain_info.agents)
        feed_dict[self.model.memory_in] = self.retrieve_memories(brain_info.agents)
    if self.use_continuous_act:
        epsilon = np.random.normal(size=(len(brain_info.vector_observations), self.model.act_size[0]))
        feed_dict[self.model.epsilon] = epsilon
    feed_dict = self.fill_eval_dict(feed_dict, brain_info)
    run_out = self._execute_model(feed_dict, self.inference_dict)
    if self.use_continuous_act:
        run_out['random_normal_epsilon'] = epsilon
    return run_out
Evaluates policy for the agent experiences provided.
:param brain_info: BrainInfo object containing inputs.
:return: Outputs from network as defined by self.inference_dict.
@timed
def evaluate(self, brain_info):
    '\n        Evaluates policy for the agent experiences provided.\n        :param brain_info: BrainInfo object containing inputs.\n        :return: Outputs from network as defined by self.inference_dict.\n        '
    feed_dict = {self.model.batch_size: len(brain_info.vector_observations), self.model.sequence_length: 1}
    epsilon = None
    if self.use_recurrent:
        if (not self.use_continuous_act):
            feed_dict[self.model.prev_action] = self.retrieve_previous_action(brain_info.agents)
        feed_dict[self.model.memory_in] = self.retrieve_memories(brain_info.agents)
    if self.use_continuous_act:
        epsilon = np.random.normal(size=(len(brain_info.vector_observations), self.model.act_size[0]))
        feed_dict[self.model.epsilon] = epsilon
    feed_dict = self.fill_eval_dict(feed_dict, brain_info)
    run_out = self._execute_model(feed_dict, self.inference_dict)
    if self.use_continuous_act:
        run_out['random_normal_epsilon'] = epsilon
    return run_out