How to use the cupy.testing.for_all_dtypes function in cupy

    @testing.for_all_dtypes()
    @testing.numpy_cupy_allclose()
    def test_sum_axis(self, xp, dtype):
        a = testing.shaped_arange((2, 3, 4), xp, dtype)
        return a.sum(axis=1)

    @testing.for_all_dtypes()
    @testing.numpy_cupy_allclose(atol=1e-5)
    def check_binary(self, name, xp, dtype, no_bool=False):
        if no_bool and numpy.dtype(dtype).char == '?':
            return numpy.int_(0)
        a = testing.shaped_arange((2, 3), xp, dtype)
        b = testing.shaped_reverse_arange((2, 3), xp, dtype)
        return getattr(xp, name)(a, b)

    @testing.for_all_dtypes()
    @testing.numpy_cupy_array_equal()
    def test_adv_getitem(self, xp, dtype):
        a = testing.shaped_arange(self.shape, xp, dtype)
        if self.transpose:
            a = a.transpose(self.transpose)
        return a[self.indexes]

    @testing.for_all_dtypes(no_bool=True)
    @testing.numpy_cupy_array_equal()
    def test_linspace(self, xp, dtype):
        return xp.linspace(0, 10, 5, dtype=dtype)

    @testing.for_all_dtypes()
    @testing.numpy_cupy_allclose()
    def test_external_trace(self, xp, dtype):
        a = testing.shaped_arange((2, 3, 4, 5), xp, dtype)
        return xp.trace(a, 1, 3, 2)

    @testing.for_all_dtypes()
    def test_scan(self, dtype):
        element_num = 10000

        if dtype in {cupy.int8, cupy.uint8}:
            element_num = 100

        a = cupy.ones((element_num,), dtype=dtype)
        prefix_sum = cupy.core.core.scan(a)
        expect = cupy.arange(start=1, stop=element_num + 1).astype(dtype)

        testing.assert_array_equal(prefix_sum, expect)

    @testing.for_all_dtypes()
    def check_savez(self, savez, dtype):
        a1 = testing.shaped_arange((2, 3, 4), dtype=dtype)
        a2 = testing.shaped_arange((3, 4, 5), dtype=dtype)

        sio = six.BytesIO()
        savez(sio, a1, a2)
        s = sio.getvalue()
        sio.close()

        sio = six.BytesIO(s)
        with cupy.load(sio) as d:
            b1 = d['arr_0']
            b2 = d['arr_1']
        sio.close()

        testing.assert_array_equal(a1, b1)

    @testing.for_all_dtypes()
    @testing.numpy_cupy_array_equal()
    def test_fill(self, xp, dtype):
        a = testing.shaped_arange((2, 3, 4), xp, dtype)
        a.fill(1)
        return a

    @testing.for_all_dtypes()
    def test_broadcast_to_fail_numpy19(self, dtype):
        # Note that broadcast_to is only supported on numpy>=1.10
        a = testing.shaped_arange((3, 1, 4), cupy, dtype)
        with self.assertRaises(ValueError):
            cupy.broadcast_to(a, (1, 3, 4))

    @testing.for_all_dtypes(name='dtype')
    @testing.numpy_cupy_array_equal()
    def test_concatenate1(self, xp, dtype):
        a = testing.shaped_arange((2, 3, 4), xp, dtype)
        b = testing.shaped_reverse_arange((2, 3, 2), xp, dtype)
        c = testing.shaped_arange((2, 3, 3), xp, dtype)
        return xp.concatenate((a, b, c), axis=2)