old_contents: import unittest
  
  import numpy
  
  import chainer
  from chainer import cuda
  from chainer import testing
  from chainer.testing import attr
  
  
  class TestDummyDeviceType(unittest.TestCase):
  
      def test_int(self):
          self.assertEqual(int(cuda.DummyDeviceType()), -1)
  
      def test_eq(self):
          self.assertEqual(cuda.DummyDeviceType(), cuda.DummyDeviceType())
  
      def test_ne(self):
          self.assertNotEqual(cuda.DummyDeviceType(), 1)
  
  
  class TestCuda(unittest.TestCase):
  
      def test_get_dummy_device(self):
          if not cuda.available:
              self.assertIs(cuda.get_device(), cuda.DummyDevice)
  
      @attr.gpu
      def test_get_dummy_device_for_empty_array(self):
          x = cuda.cupy.array([]).reshape((0, 10))
          self.assertIs(cuda.get_device(x), cuda.DummyDevice)
  
      def test_to_gpu_unavailable(self):
          x = numpy.array([1])
          if not cuda.available:
              with self.assertRaises(RuntimeError):
                  cuda.to_gpu(x)
  
      def test_empy_unavailable(self):
          if not cuda.available:
              with self.assertRaises(RuntimeError):
                  cuda.empty(())
  
      def test_empy_like_unavailable(self):
          x = numpy.array([1])
          if not cuda.available:
              with self.assertRaises(RuntimeError):
                  cuda.empty_like(x)
  
  
  class TestToCPU(unittest.TestCase):
  
      def setUp(self):
          self.x = numpy.random.uniform(-1, 1, (2, 3))
  
      def test_numpy_array(self):
          y = cuda.to_cpu(self.x)
          self.assertIs(self.x, y)  # Do not copy
  
      @attr.gpu
      def test_cupy_array(self):
          x = cuda.to_gpu(self.x)
          y = cuda.to_cpu(x)
          self.assertIsInstance(y, numpy.ndarray)
          numpy.testing.assert_array_equal(self.x, y)
  
      def test_variable(self):
          x = numpy.random.uniform(-1, 1, (2, 3))
          x = chainer.Variable(x)
          with self.assertRaises(TypeError):
              cuda.to_cpu(x)
  
  
  testing.run_module(__name__, __file__)
  
new_contents: import unittest
  
  import numpy
  
  import chainer
  from chainer import cuda
  from chainer import testing
  from chainer.testing import attr
  
  
  class TestDummyDeviceType(unittest.TestCase):
  
      def test_int(self):
          self.assertEqual(int(cuda.DummyDeviceType()), -1)
  
      def test_eq(self):
          self.assertEqual(cuda.DummyDeviceType(), cuda.DummyDeviceType())
  
      def test_ne(self):
          self.assertNotEqual(cuda.DummyDeviceType(), 1)
  
  
  class TestCuda(unittest.TestCase):
  
      def test_get_dummy_device(self):
          if not cuda.available:
              self.assertIs(cuda.get_device(), cuda.DummyDevice)
  
      @attr.gpu
      def test_get_dummy_device_for_empty_array(self):
          x = cuda.cupy.array([]).reshape((0, 10))
          self.assertIs(cuda.get_device(x), cuda.DummyDevice)
  
      def test_to_gpu_unavailable(self):
          x = numpy.array([1])
          if not cuda.available:
              with self.assertRaises(RuntimeError):
                  cuda.to_gpu(x)
  
      def test_empy_unavailable(self):
          if not cuda.available:
              with self.assertRaises(RuntimeError):
                  cuda.empty(())
  
      def test_empy_like_unavailable(self):
          x = numpy.array([1])
          if not cuda.available:
              with self.assertRaises(RuntimeError):
                  cuda.empty_like(x)
  
  
  @testing.parameterize(
      {'c_contiguous': True},
      {'c_contiguous': False},
  )
  class TestToCPU(unittest.TestCase):
  
      def setUp(self):
          self.x = numpy.random.uniform(-1, 1, (2, 3))
  
      def test_numpy_array(self):
          y = cuda.to_cpu(self.x)
          self.assertIs(self.x, y)  # Do not copy
  
      @attr.gpu
      def test_cupy_array(self):
          x = cuda.to_gpu(self.x)
          if not self.c_contiguous:
              x = cuda.cupy.asfortranarray(x)
          y = cuda.to_cpu(x)
          self.assertIsInstance(y, numpy.ndarray)
          numpy.testing.assert_array_equal(self.x, y)
  
      def test_variable(self):
          x = chainer.Variable(self.x)
          with self.assertRaises(TypeError):
              cuda.to_cpu(x)
  
  
  testing.run_module(__name__, __file__)
  
subject: Improve test for to_cpu