import unittest

from cupy import testing


@testing.parameterize(
    {'shape': (2, 3, 4), 'transpose': None, 'indexes': (1, 0, 2)},
    {'shape': (2, 3, 4), 'transpose': None, 'indexes': (-1, 0, -2)},
    {'shape': (2, 3, 4), 'transpose': (2, 0, 1), 'indexes': (1, 0, 2)},
    {'shape': (2, 3, 4), 'transpose': (2, 0, 1), 'indexes': (-1, 0, -2)},
    {'shape': (2, 3, 4), 'transpose': None,
     'indexes': (slice(None), slice(None, 1), slice(2))},
    {'shape': (2, 3, 4), 'transpose': None,
     'indexes': (slice(None), slice(None, -1), slice(-2))},
    {'shape': (2, 3, 4), 'transpose': (2, 0, 1),
     'indexes': (slice(None), slice(None, 1), slice(2))},
    {'shape': (2, 3, 5), 'transpose': None,
     'indexes': (slice(None, None, -1), slice(1, None, -1), slice(4, 1, -2))},
    {'shape': (2, 3, 5), 'transpose': (2, 0, 1),
     'indexes': (slice(4, 1, -2), slice(None, None, -1), slice(1, None, -1))},
    {'shape': (2, 3, 4), 'transpose': None, 'indexes': (Ellipsis, 2)},
    {'shape': (2, 3, 4), 'transpose': None, 'indexes': (1, Ellipsis)},
    {'shape': (2, 3, 4, 5), 'transpose': None, 'indexes': (1, Ellipsis, 3)},
    {'shape': (2, 3, 4), 'transpose': None,
     'indexes': (1, None, slice(2), None, 2)},
    {'shape': (2, 3), 'transpose': None, 'indexes': (None,)},
    {'shape': (2,), 'transpose': None, 'indexes': (slice(None,), None)},
    {'shape': (), 'transpose': None, 'indexes': (None,)},
    {'shape': (), 'transpose': None, 'indexes': (None, None)},
)
@testing.gpu
class TestArrayIndexingParameterized(unittest.TestCase):

    _multiprocess_can_split_ = True

    @testing.for_all_dtypes()
    @testing.numpy_cupy_array_equal()
    def test_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.parameterize(
    {'shape': (), 'transpose': None, 'indexes': 0},
    {'shape': (), 'transpose': None, 'indexes': (slice(0, 1, 0),)},
    {'shape': (2, 3), 'transpose': None, 'indexes': (0, 0, 0)},
    {'shape': (2, 3, 4), 'transpose': None, 'indexes': -3},
    {'shape': (2, 3, 4), 'transpose': (2, 0, 1), 'indexes': -5},
    {'shape': (2, 3, 4), 'transpose': None, 'indexes': 3},
    {'shape': (2, 3, 4), 'transpose': (2, 0, 1), 'indexes': 5},
    {'shape': (2, 3, 4), 'transpose': None,
     'indexes': (slice(0, 1, 0), )},
    {'shape': (2, 3, 4), 'transpose': None,
     'indexes': (slice((0, 0), None, None), )},
    {'shape': (2, 3, 4), 'transpose': None,
     'indexes': (slice(None, (0, 0), None), )},
    {'shape': (2, 3, 4), 'transpose': None,
     'indexes': (slice(None, None, (0, 0)), )},
)
@testing.gpu
class TestArrayInvalidIndex(unittest.TestCase):

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


@testing.gpu
class TestArrayIndex(unittest.TestCase):

    _multiprocess_can_split_ = True

    @testing.for_all_dtypes()
    @testing.numpy_cupy_array_equal()
    def test_setitem_constant(self, xp, dtype):
        a = xp.zeros((2, 3, 4), dtype=dtype)
        a[:] = 1
        return a

    @testing.for_all_dtypes()
    @testing.numpy_cupy_array_equal()
    def test_setitem_partial_constant(self, xp, dtype):
        a = xp.zeros((2, 3, 4), dtype=dtype)
        a[1, 1:3] = 1
        return a

    @testing.for_all_dtypes()
    @testing.numpy_cupy_array_equal()
    def test_setitem_copy(self, xp, dtype):
        a = xp.zeros((2, 3, 4), dtype=dtype)
        b = testing.shaped_arange((2, 3, 4), xp, dtype)
        a[:] = b
        return a

    @testing.for_all_dtypes()
    @testing.numpy_cupy_array_equal()
    def test_setitem_partial_copy(self, xp, dtype):
        a = xp.zeros((2, 3, 4), dtype=dtype)
        b = testing.shaped_arange((3, 2), xp, dtype)
        a[1, ::-1, 1:4:2] = b
        return a

    @testing.numpy_cupy_array_equal()
    def test_T(self, xp):
        a = testing.shaped_arange((2, 3, 4), xp)
        return a.T

    @testing.numpy_cupy_array_equal()
    def test_T_vector(self, xp):
        a = testing.shaped_arange((4,), xp)
        return a.T

@@ -1468,24 +1468,322 @@
 ne, None)%7D,%0A
+    %7B'shape': (10,), 'transpose': None, 'indexes': (slice(10, -9, -1),)%7D,%0A    %7B'shape': (10,), 'transpose': None, 'indexes': (slice(-1, -11, -1),)%7D,%0A    %7B'shape': (10,), 'transpose': None, 'indexes': (slice(10, -9, -3),)%7D,%0A    %7B'shape': (10,), 'transpose': None, 'indexes': (slice(-1, -11, -3),)%7D,%0A
 )%0A@testing.g

Add negative stride test