def test_device_broadcast(self):

        a = np.random.randn(100, 3, 1)
        b = a.transpose(2, 1, 0)

        def fn(a, b):
            return a - b

        @vectorize(['float64(float64,float64)'], target='cuda')
        def fngpu(a, b):
            return a - b

        expect = fn(a, b)
        got = fngpu(cuda.to_device(a), cuda.to_device(b))
        np.testing.assert_almost_equal(expect, got.copy_to_host())
Same test as .test_broadcast_bug_90() but with device array as inputs
dataset/ETHPy150Open numba/numba/numba/cuda/tests/cudapy/test_vectorize_decor.py/TestGPUVectorizeBroadcast.test_device_broadcast