code: def test_to_device(
      *,
      dtype_and_x,
      stream,
      test_flags,
      backend_fw,
      on_device,
  ):
      dtype, x = dtype_and_x
      dtype = dtype[0]
      x = x[0]
  
      with BackendHandler.update_backend(backend_fw) as ivy_backend:
          x = ivy_backend.asarray(x)
          if test_flags.as_variable and ivy_backend.is_float_dtype(
              dtype
          ):
              x = ivy_backend.functional.ivy.gradients._variable(x)
  
          # create a dummy array for out that is broadcastable to x
          out = (
              ivy_backend.zeros(
                  ivy_backend.shape(x), device=on_device, dtype=dtype
              )
              if test_flags.with_out
              else None
          )
  
          device = ivy_backend.dev(x)
          x_on_dev = ivy_backend.to_device(
              x, on_device, stream=stream, out=out
          )
          dev_from_new_x = ivy_backend.dev(x_on_dev)
  
          if test_flags.with_out:
              # should be the same array test
              assert x_on_dev is out
  
              # should be the same device
              if backend_fw != "paddle":
                  assert ivy_backend.dev(
                      x_on_dev, as_native=True
                  ) == ivy_backend.dev(out, as_native=True)
              else:
                  assert ivy_backend.dev(
                      x_on_dev, as_native=False
                  ) == ivy_backend.dev(out, as_native=False)
  
              # check if native arrays are the same
              # these backends do not support native inplace updates
              assume(backend_fw not in ["tensorflow", "jax"])
  
              assert x_on_dev.data is out.data
  
          # value test
          if backend_fw == "tensorflow":
              assert "/" + ":".join(
                  dev_from_new_x[1:].split(":")[-2:]
              ) == "/" + ":".join(device[1:].split(":")[-2:])
          elif backend_fw == "torch":
              assert type(dev_from_new_x) == type(device)  # noqa: E721
          else:
              assert dev_from_new_x == device
  
          # array instance test
          assert x.to_device(device).dev() == device
          # container instance test
          container_x = ivy_backend.Container({"x": x})
          assert container_x.to_device(device).dev() == device
          # container static test
          assert (
              ivy_backend.Container.to_device(container_x, device).dev()
              == device
          )
  
imports: import io
  import multiprocessing
  import os
  import re
  import shutil
  import sys
  import warnings
  import numpy
  import psutil
  import subprocess
  from hypothesis import strategies, assume
  import ivy
  import ivy_tests.test_ivy.helpers
  import ivy_tests.test_ivy.helpers.globals
  from ivy_tests.test_ivy.helpers import handle_test, BackendHandler
label_desc: Use image node_id 27 for calling a global function with example usage: test_to_device() without return types