fix test_elementwise

Author: vtavana

dpnp/dpnp_algo/dpnp_elementwise_common.py

@@ -595,7 +595,7 @@ def __call__(self, x, decimals=0, out=None, dtype=None):
 
             out_usm = None if out is None else dpnp.get_usm_ndarray(out)
             # the output of x_usm multiplied by 10^decimals should be
-            # float avoid overflow for integer dtypes
+            # float to avoid overflow for integer dtypes
             x_usm = dpt.multiply(x_usm, float(10**decimals))
             x_usm = dpt.round(x_usm, out=out_usm)
             res_usm = dpt.divide(x_usm, 10**decimals, out=out_usm)

dpnp/tests/third_party/cupy/core_tests/test_elementwise.py

@@ -110,7 +110,7 @@ def test_large_int_upper_2(self, xp, dtype):
             if xp.issubdtype(dtype, xp.unsignedinteger) or flag:
                 pytest.skip("numpy doesn't raise OverflowError")
 
-            if dtype == xp.int8 and is_win_platform():
+            if dtype in [xp.int8, xp.intc] and is_win_platform():
                 pytest.skip("numpy promotes dtype differently")
 
         a = xp.array([1], dtype=xp.int8)
@@ -160,12 +160,11 @@ def test_large_int_lower_1(self, xp, dtype):
             if dtype in [xp.int16, xp.int32, xp.int64, xp.longlong]:
                 pytest.skip("numpy doesn't raise OverflowError")
 
-            if dtype == xp.int8 and is_win_platform():
+            if dtype in [xp.int8, xp.intc] and is_win_platform():
                 pytest.skip("numpy promotes dtype differently")
 
         a = xp.array([0], dtype=xp.int8)
         b = xp.iinfo(dtype).min
-        res = a + b
         return a + b
 
     @testing.for_int_dtypes(no_bool=True)
@@ -175,7 +174,7 @@ def test_large_int_lower_2(self, xp, dtype):
             if dtype in [xp.int16, xp.int32, xp.int64, xp.longlong]:
                 pytest.skip("numpy doesn't raise OverflowError")
 
-            if dtype == xp.int8 and is_win_platform():
+            if dtype in [xp.int8, xp.intc] and is_win_platform():
                 pytest.skip("numpy promotes dtype differently")
 
         a = xp.array([-1], dtype=xp.int8)