def test_basic(self):
        """Basic test that makes sure that vector type and aliases
        are available within the cuda module from both device and
        simulator mode. This is an important sanity check, since other
        tests below tests the vector type objects programmatically.
        """
        @cuda.jit("void(float64[:])")
        def kernel(arr):
            v1 = cuda.float64x4(1.0, 3.0, 5.0, 7.0)
            v2 = cuda.short2(10, 11)
            arr[0] = v1.x
            arr[1] = v1.y
            arr[2] = v1.z
            arr[3] = v1.w
            arr[4] = v2.x
            arr[5] = v2.y

        res = np.zeros(6, dtype=np.float64)
        kernel[1, 1](res)
        self.assertTrue(np.allclose(res, [1.0, 3.0, 5.0, 7.0, 10, 11]))
Basic test that makes sure that vector type and aliases
        are available within the cuda module from both device and
        simulator mode. This is an important sanity check, since other
        tests below tests the vector type objects programmatically.
        
numba/cuda/tests/cudapy/test_vector_type.py