code: def begin_episode(self, agent_indices):
      
      with tf.name_scope('begin_episode/'):
        if self._last_state is None:
          reset_state = tf.no_op()
        else:
          reset_state = utility.reinit_nested_vars(
              self._last_state, agent_indices)
        reset_buffer = self._current_episodes.clear(agent_indices)
        with tf.control_dependencies([reset_state, reset_buffer]):
          return tf.constant('')
docs: Reset the recurrent states and stored episode.
  
      Args:
        agent_indices: Tensor containing current batch indices.
  
      Returns:
        Summary tensor.