code: def to_gpu(array, device=None, stream=None):
      """Copies the given CPU array to the specified device.
  
      Args:
          array (*array*, None, list or tuple):
              Array or arrays to be sent to GPU.
          device: CUDA device specifier. If ``None`` or :data:`cuda.DummyDevice`,
              the arrays will be copied to the current CUDA device.
          stream (~cupy.cuda.Stream): *(deprecated since v3.0.0)*
              CUDA stream. If not ``None``, the copy runs asynchronously.
  
      Returns:
          cupy.ndarray, list or tuple: Array or arrays on GPU.
  
          If some of the arrays are already on GPU, then this function just
          returns those arrays without performing any copy.
  
          If input arrays include `None`, it is returned as `None` as is.
  
      """
      if stream is not None:
          warnings.warn(
              "The stream option is deprecated in chainer.backends.cuda.to_gpu. "
              "Please remove it.",
              DeprecationWarning,
          )
  
      check_cuda_available()
      if device is DummyDevice:
          device = cuda.Device()
      else:
          device = _get_device_or_current(device)
  
      return _backend._convert_arrays(
          array, lambda arr: _array_to_gpu(arr, device, 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 7 for calling a global function with example usage: to_gpu(array, device, stream) and returns: _backend