Align sum and prod tests

Author: antonwolfy

tests/test_arithmetic.py

@@ -6,15 +6,6 @@
 from tests.third_party.cupy import testing
 
 
-# Note: numpy.sum() always upcast integers to (u)int64 and float32 to
-# float64 for dtype=None. `np.sum` does that too for integers, but not for
-# float32, so we need to special-case it for these tests
-def _get_dtype_kwargs(xp, dtype):
-    if xp is numpy and dtype == numpy.float32 and has_support_aspect64():
-        return {"dtype": numpy.float64}
-    return {}
-
-
 class TestArithmetic(unittest.TestCase):
     @testing.for_float_dtypes()
     @testing.numpy_cupy_allclose()
@@ -42,7 +33,7 @@ def test_nanprod(self, xp, dtype):
     @testing.numpy_cupy_allclose()
     def test_nansum(self, xp, dtype):
         a = xp.array([-2.5, -1.5, xp.nan, 10.5, 1.5, xp.nan], dtype=dtype)
-        return xp.nansum(a, **_get_dtype_kwargs(xp, a.dtype))
+        return xp.nansum(a)
 
     @testing.for_float_dtypes()
     @testing.numpy_cupy_allclose()

tests/test_sum.py

@@ -61,10 +61,7 @@ def test_sum_axis():
     ia = dpnp.array(a)
 
     result = dpnp.sum(ia, axis=1)
-    if has_support_aspect64():
-        expected = numpy.sum(a, axis=1, dtype=numpy.float64)
-    else:
-        expected = numpy.sum(a, axis=1)
+    expected = numpy.sum(a, axis=1)
     assert_array_equal(expected, result)
 
 

tests/third_party/cupy/math_tests/test_sumprod.py

@@ -6,15 +6,6 @@
 from tests.third_party.cupy import testing
 
 
-# Note: numpy.sum() always upcast integers to (u)int64 and float32 to
-# float64 for dtype=None. `np.sum` does that too for integers, but not for
-# float32, so we need to special-case it for these tests
-def _get_dtype_kwargs(xp, dtype):
-    if xp is numpy and dtype == numpy.float32 and has_support_aspect64():
-        return {"dtype": numpy.float64}
-    return {}
-
-
 class TestSumprod:
     def tearDown(self):
         # Free huge memory for slow test
@@ -26,43 +17,43 @@ def tearDown(self):
     @testing.numpy_cupy_allclose()
     def test_sum_all(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4), xp, dtype)
-        return a.sum(**_get_dtype_kwargs(xp, dtype))
+        return a.sum()
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose()
     def test_sum_all_keepdims(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4), xp, dtype)
-        return a.sum(**_get_dtype_kwargs(xp, dtype), keepdims=True)
+        return a.sum(keepdims=True)
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose()
     def test_external_sum_all(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4), xp, dtype)
-        return xp.sum(a, **_get_dtype_kwargs(xp, dtype))
+        return xp.sum(a)
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose(rtol=1e-06)
     def test_sum_all2(self, xp, dtype):
         a = testing.shaped_arange((20, 30, 40), xp, dtype)
-        return a.sum(**_get_dtype_kwargs(xp, dtype))
+        return a.sum()
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose()
     def test_sum_all_transposed(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4), xp, dtype).transpose(2, 0, 1)
-        return a.sum(**_get_dtype_kwargs(xp, dtype))
+        return a.sum()
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose(rtol=1e-06)
     def test_sum_all_transposed2(self, xp, dtype):
         a = testing.shaped_arange((20, 30, 40), xp, dtype).transpose(2, 0, 1)
-        return a.sum(**_get_dtype_kwargs(xp, dtype))
+        return a.sum()
 
     @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(**_get_dtype_kwargs(xp, dtype), axis=1)
+        return a.sum(axis=1)
 
     @testing.slow
     @testing.numpy_cupy_allclose()
@@ -74,57 +65,57 @@ def test_sum_axis_huge(self, xp):
     @testing.numpy_cupy_allclose()
     def test_external_sum_axis(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4), xp, dtype)
-        return xp.sum(a, **_get_dtype_kwargs(xp, dtype), axis=1)
+        return xp.sum(a, axis=1)
 
     # float16 is omitted, since NumPy's sum on float16 arrays has more error
     # than CuPy's.
     @testing.for_all_dtypes(no_float16=True)
     @testing.numpy_cupy_allclose()
     def test_sum_axis2(self, xp, dtype):
         a = testing.shaped_arange((20, 30, 40), xp, dtype)
-        return a.sum(**_get_dtype_kwargs(xp, dtype), axis=1)
+        return a.sum(axis=1)
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose(contiguous_check=False)
     def test_sum_axis_transposed(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4), xp, dtype).transpose(2, 0, 1)
-        return a.sum(**_get_dtype_kwargs(xp, dtype), axis=1)
+        return a.sum(axis=1)
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose(contiguous_check=False)
     def test_sum_axis_transposed2(self, xp, dtype):
         a = testing.shaped_arange((20, 30, 40), xp, dtype).transpose(2, 0, 1)
-        return a.sum(**_get_dtype_kwargs(xp, dtype), axis=1)
+        return a.sum(axis=1)
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose()
     def test_sum_axes(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4, 5), xp, dtype)
-        return a.sum(**_get_dtype_kwargs(xp, dtype), axis=(1, 3))
+        return a.sum(axis=(1, 3))
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose(rtol=1e-4)
     def test_sum_axes2(self, xp, dtype):
         a = testing.shaped_arange((20, 30, 40, 50), xp, dtype)
-        return a.sum(**_get_dtype_kwargs(xp, dtype), axis=(1, 3))
+        return a.sum(axis=(1, 3))
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose(rtol=1e-6)
     def test_sum_axes3(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4, 5), xp, dtype)
-        return a.sum(**_get_dtype_kwargs(xp, dtype), axis=(0, 2, 3))
+        return a.sum(axis=(0, 2, 3))
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose(rtol=1e-6)
     def test_sum_axes4(self, xp, dtype):
         a = testing.shaped_arange((20, 30, 40, 50), xp, dtype)
-        return a.sum(**_get_dtype_kwargs(xp, dtype), axis=(0, 2, 3))
+        return a.sum(axis=(0, 2, 3))
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose()
     def test_sum_empty_axis(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4, 5), xp, dtype)
-        return a.sum(**_get_dtype_kwargs(xp, dtype), axis=())
+        return a.sum(axis=())
 
     @testing.for_all_dtypes_combination(names=["src_dtype", "dst_dtype"])
     @testing.numpy_cupy_allclose()
@@ -142,7 +133,7 @@ def test_sum_keepdims_and_dtype(self, xp, src_dtype, dst_dtype):
     @testing.numpy_cupy_allclose()
     def test_sum_keepdims_multiple_axes(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4), xp, dtype)
-        return a.sum(**_get_dtype_kwargs(xp, dtype), axis=(1, 2), keepdims=True)
+        return a.sum(axis=(1, 2), keepdims=True)
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose()
@@ -162,25 +153,25 @@ def test_sum_out_wrong_shape(self):
     @testing.numpy_cupy_allclose()
     def test_prod_all(self, xp, dtype):
         a = testing.shaped_arange((2, 3), xp, dtype)
-        return a.prod(**_get_dtype_kwargs(xp, dtype))
+        return a.prod()
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose()
     def test_external_prod_all(self, xp, dtype):
         a = testing.shaped_arange((2, 3), xp, dtype)
-        return xp.prod(a, **_get_dtype_kwargs(xp, dtype))
+        return xp.prod(a)
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose()
     def test_prod_axis(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4), xp, dtype)
-        return a.prod(axis=1, **_get_dtype_kwargs(xp, dtype))
+        return a.prod(axis=1)
 
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose()
     def test_external_prod_axis(self, xp, dtype):
         a = testing.shaped_arange((2, 3, 4), xp, dtype)
-        return xp.prod(a, axis=1, **_get_dtype_kwargs(xp, dtype))
+        return xp.prod(a, axis=1)
 
     @testing.for_all_dtypes_combination(names=["src_dtype", "dst_dtype"])
     @testing.numpy_cupy_allclose()
@@ -228,12 +219,7 @@ def _test(self, xp, dtype):
         if not issubclass(dtype, xp.integer):
             a[:, 1] = xp.nan
         func = getattr(xp, self.func)
-        return func(
-            a,
-            **_get_dtype_kwargs(xp, dtype),
-            axis=self.axis,
-            keepdims=self.keepdims,
-        )
+        return func(a, axis=self.axis, keepdims=self.keepdims)
 
     @testing.for_all_dtypes(no_bool=True, no_float16=True)
     @testing.numpy_cupy_allclose(type_check=has_support_aspect64())
@@ -299,15 +285,15 @@ def test_nansum_axes(self, xp, dtype):
         a = testing.shaped_arange(self.shape, xp, dtype)
         if not issubclass(dtype, xp.integer):
             a[:, 1] = xp.nan
-        return xp.nansum(a, **_get_dtype_kwargs(xp, dtype), axis=self.axis)
+        return xp.nansum(a, axis=self.axis)
 
 
 class TestNansumNanprodHuge:
     def _test(self, xp, nan_slice):
         a = testing.shaped_random((2048, 1, 1024), xp, "f")
         a[nan_slice] = xp.nan
         a = xp.broadcast_to(a, (2048, 256, 1024))
-        return xp.nansum(a, **_get_dtype_kwargs(xp, a.dtype), axis=2)
+        return xp.nansum(a, axis=2)
 
     @testing.slow
     @testing.numpy_cupy_allclose(atol=1e-1)