code: def split_one_step_batch_input(xs):
      """Split one-step batch input.
  
      Args:
          xs (chainer.Variable, ndarray or tuple): One-step batched input. It
              should be either:
                  - a variable whose first axis is the batch axis.
                  - a tuple of such variables.
  
      Returns:
          list: Either a list of variables or a list of tuples of varialbes.
              The length of the list is the batch size of the input.
      """
      if isinstance(xs, tuple):
          return list(zip(*[split_one_step_batch_input(x) for x in xs]))
      else:
          return list(F.split_axis(xs, len(xs), axis=0))
  
imports: from cached_property import cached_property
  import chainer
  import chainer.functions
  import chainer.links
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: split_one_step_batch_input(xs) and returns: list, list