code: def create_multi_node_n_step_rnn(
      actual_link, communicator, rank_in=None, rank_out=None
  ):
      """Create a multi node stacked RNN link from a Chainer stacked RNN link.
  
      Multi node stacked RNN link is used for model-parallel.
      The created link will receive initial hidden states from the process
      specified by ``rank_in`` (or do not receive if ``None``), execute
      the original RNN compuation, and then send resulting hidden states
      to the process specified by ``rank_out``.
  
      Compared with Chainer stacked RNN link, multi node stacked RNN link
      returns an extra object called ``delegate_variable``.
      If ``rank_out`` is not ``None``, backward computation is expected
      to be begun from ``delegate_variable``.
      For detail, please refer ``chainermn.functions.pseudo_connect``.
  
      The following RNN links can be passed to this function:
  
      - ``chainer.links.NStepBiGRU``
      - ``chainer.links.NStepBiLSTM``
      - ``chainer.links.NStepBiRNNReLU``
      - ``chainer.links.NStepBiRNNTanh``
      - ``chainer.links.NStepGRU``
      - ``chainer.links.NStepLSTM``
      - ``chainer.links.NStepRNNReLU``
      - ``chainer.links.NStepRNNTanh``
  
      Args:
          link (chainer.Link): Chainer stacked RNN link
          communicator: ChainerMN communicator
          rank_in (int, or None):
              Rank of the process which sends hidden RNN states to this process.
          rank_out (int, or None):
              Rank of the process to which this process sends hiddne RNN states.
  
      Returns:
          The multi node stacked RNN link based on ``actual_link``.
      """
      chainer.utils.experimental(
          "chainermn.links.create_multi_node_n_step_rnn"
      )
      return _MultiNodeNStepRNN(
          actual_link, communicator, rank_in, rank_out
      )
  
file_path: chainer/chainermn/links/n_step_rnn.py
imports: import chainer
  import chainer.links.rnn
  import chainermn.functions
label_desc: Use image node_id 1 for calling a global function with example usage: create_multi_node_n_step_rnn(actual_link, communicator, rank_in, rank_out) and returns: _MultiNodeNStepRNN