def METHOD_NAME(self):
    # Peer access is not always possible - for example, with one GPU in TCC
    # mode and one in WDDM - if that is the case, this test would fail so
    # we need to skip it.
    with cuda.gpus[0]:
        ctx = cuda.current_context()
        if not ctx.can_access_peer(1):
            self.skipTest('Peer access between GPUs disabled')
    # 1. Create a range in an array
    hostarr = np.arange(10, dtype=np.float32)
    # 2. Copy range array from host -> GPU 0
    with cuda.gpus[0]:
        arr1 = cuda.to_device(hostarr)
    # 3. Initialize a zero-filled array on GPU 1
    with cuda.gpus[1]:
        arr2 = cuda.to_device(np.zeros_like(hostarr))
    with cuda.gpus[0]:
        # 4. Copy range from GPU 0 -> GPU 1
        arr2.copy_to_device(arr1)
        # 5. Copy range from GPU 1 -> host and check contents
        np.testing.assert_equal(arr2.copy_to_host(), hostarr)