code: def copy(x, dst):
      """Copies the input variable onto the specified device.
  
      If the input ``x`` already resides on the device specified by ``dst``, no
      copy will actually take place and the returned variable will hold a view
      of the input. In other cases, the input will be copied to ``dst``.
      When ``dst == -1``, the array is copied to the host memory.
      This function supports copies from host to host, from host to device,
      from device to device and from device to host.
  
      Args:
          x (:class:`~chainer.Variable` or :ref:`ndarray`):
              Variable to be copied.
          dst: Target device specifier.
  
      Returns:
          ~chainer.Variable: Output variable.
  
      .. admonition:: Example
  
          >>> import chainer.backends.cuda as cuda
          >>> x_arr = np.random.uniform(-1, 1, (5, 10))
          >>> x = chainer.Variable(x_arr)
          >>> x.device
          <CpuDevice (numpy)>
          >>> y = F.copy(x, '@cupy:0') # from CPU (NumPy) to GPU 0 (CuPy)
          >>> y.device
          <GpuDevice (cupy):0>
  
      .. note::
          Copies between non-ChainerX devices and ChainerX devices are not
          supported.
  
      """
      # For backward compatibility
      if dst is cuda.DummyDevice:
          dst = chainer.get_device("@numpy")
  
      x_is_var = isinstance(x, chainer.Variable)
      in_device = backend.get_device_from_array(
          x.array if x_is_var else x
      )
      out_device = chainer.get_device(dst)
  
      if in_device.xp is chainerx:
          x_arr = x.chx_array if x_is_var else x
          if out_device.xp is not chainerx:
              # ChainerX to non-ChainerX
              if x_arr.is_backprop_required():
                  raise RuntimeError(
                      "F.copy does not support copy from a ChainerX array with "
                      "backprop required to a non-ChainerX device.\n"
                      "From: {}\n"
                      "To: {}".format(in_device, out_device)
                  )
              return chainer.Variable(
                  out_device.send(x_arr), requires_grad=False
              )
  
          # ChainerX to ChainerX
          return chainer.Variable(
              out_device.send(x_arr),
              requires_grad=x_arr.is_backprop_required(),
          )
  
      if out_device.xp is chainerx:
          # Non-ChainerX to ChainerX
          if x_is_var and x.requires_grad:
              raise RuntimeError(
                  "F.copy does not support copy from a non-ChainerX array with "
                  "backprop required to a ChainerX device.\n"
                  "From: {}\n"
                  "To: {}".format(in_device, out_device)
              )
          x_arr = x.array if x_is_var else x
          return chainer.Variable(
              out_device.send(x_arr), requires_grad=False
          )
  
      # Non-ChainerX to non-ChainerX
      (y,) = Copy(in_device, out_device).apply((x,))
      return y
  
file_path: chainer/chainer/functions/array/copy.py
imports: import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.utils import type_check
  import chainerx
label_desc: Use image node_id 1 for calling a global function with example usage: copy(x, dst) and returns: y, chainer, chainer, chainer