class_docstr: Stateless recurrent link interface.
  
  This class defines the interface of a recurrent link ChainerRL can handle.
  
  In most casese, you can just use ChainerRL's existing containers like
  `chainerrl.links.StatelessRecurrentChainList`,
  `chainerrl.links.StatelessRecurrentSequential`, and
  `chainerrl.links.StatelessRecurrentBranched` to define a recurrent
  link. You can use Chainer's recurrent links such as L.NStepLSTM inside the
  containers.
  
  To write your own recurrent link, you need to implement the interface.
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docstr: One-step batch forward computation.
  
  Args:
      x (chainer.Variable, ndarray, or tuple): One-step batched input.
      recurrent_state (object): Batched recurrent state.
  
  Returns:
      chainer.Variable, ndarray, or tuple: One-step batched output.
      object: New batched recurrent state.
docstr_tok: ["One-step","batch","forward","computation",".","Args",":","x","(","chainer.Variable",",","ndarray",",","or","tuple",")",":","One-step","batched","input",".","recurrent_state","(","object",")",":","Batched","recurrent","state",".","Returns",":","chainer.Variable",",","ndarray",",","or","tuple",":","One-step","batched","output",".","object",":","New","batched","recurrent","state","."]
code: def __call__(self, x, recurrent_state):
      """One-step batch forward computation.
  
      Args:
          x (chainer.Variable, ndarray, or tuple): One-step batched input.
          recurrent_state (object): Batched recurrent state.
  
      Returns:
          chainer.Variable, ndarray, or tuple: One-step batched output.
          object: New batched recurrent state.
      """
      assert isinstance(x, (chainer.Variable, self.xp.ndarray))
      return self.n_step_forward(
          split_one_step_batch_input(x),
          recurrent_state,
          output_mode="concat",
      )
  
imports: from cached_property import cached_property
  import chainer
  import chainer.functions
  import chainer.links
  import numpy
label_desc: Use image node_id 2 for calling the StatelessRecurrent obj's underlying member method code with example usage: obj.__call__(x, recurrent_state) and returns: self