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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def begin_episode(self, agent_indices):
 """Reset the recurrent states and stored episode. Args: agent_indices: Tensor containing current batch indices. Returns: Summary tensor. """

    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('')