code: def to_cpu(array, stream=None):
      """Copies the given GPU array to host CPU.
  
      Args:
          array (*array*, None, list or tuple):
              Array or arrays to be sent to CPU.
          stream (cupy.cuda.Stream): CUDA stream.
  
      Returns:
          numpy.ndarray, list or tuple: Array on CPU.
  
          If some of the arrays are already on CPU, then this function just
          returns those arrays without performing any copy.
  
          If input arrays include `None`, it is returned as `None` as is.
  
      """
      return _backend._convert_arrays(
          array, lambda arr: _array_to_cpu(arr, stream)
      )
  
imports: import binascii
  import functools
  import itertools
  import os
  import threading
  import time
  import typing
  import warnings
  import numpy
  import six
  import chainer
  from chainer import _backend
  from chainer.backends import _cpu
  from chainer.backends import intel64
  from chainer.configuration import config
  from chainer import types
  import chainerx
label_desc: Use image node_id 9 for calling a global function with example usage: to_cpu(array, stream) and returns: _backend