code: def _array_from_chainerx(array):
      if array is None:
          return None
      if not isinstance(array, chainerx.ndarray):
          if isinstance(array, chainer.get_array_types()):
              return array
          raise TypeError(
              "Tried to convert to a non-ChainerX array from an invalid type: "
              "{}".format(type(array))
          )
  
      backend_name = array.device.backend.name
      if backend_name == "native":
          return _cpu._to_cpu(array)
      if backend_name == "cuda":
          return cuda.to_gpu(array, array.device.index)
  
      raise ValueError(
          "Only ChainerX arrays with native or cuda backends can be converted "
          "to non-ChainerX arrays.\nActual: {0}.".format(backend_name)
      )
  
imports: import numpy
  import chainer
  from chainer import _backend
  from chainer.backends import _cpu
  from chainer.backends import cuda
  from chainer.backends import intel64
  import chainerx
label_desc: Use image node_id 5 for calling a global function with example usage: _array_from_chainerx(array) and returns: None, _cpu, cuda, array