class_docstr: Function that splits multiple arrays along the specified axis.
code: def forward(self, inputs):
      (x,) = inputs
      self._xp = backend.get_array_module(x)
  
      # Currently iDeep only supports 4 dims
      if (
          intel64.should_use_ideep(">=auto")
          and intel64.inputs_all_ready(inputs, (4,))
          and self._ideep_is_supported(inputs)
      ):
          return self._forward_ideep(inputs)
  
      indices_or_sections = self.indices_or_sections
      ret = self._xp.split(x, indices_or_sections, self.axis)
      if self._xp == numpy and not _numpy_split_ok:
          ret = _fix_numpy_split(ret, x, indices_or_sections, self.axis)
      self._shapes = [r.shape for r in ret]
      return tuple(ret)
  
imports: import numpy
  import six
  import chainer
  from chainer import backend
  from chainer.backends import intel64
  from chainer import function_node
  from chainer.utils import collections_abc
  from chainer.utils import type_check
  import chainerx
label_desc: Use image node_id 5 for calling the SplitAxis obj's underlying member method code with example usage: obj.forward(inputs) and returns: tuple, self