Change test to verify that the correct exceptions are thrown.

python/cudf/cudf/core/dataframe.py

@@ -62,6 +62,7 @@
     "max": "nanmax",
     "sum": "nansum",
     "prod": "nanprod",
+    "product": "nanprod",
     "mean": "nanmean",
     "std": "nanstd",
     "var": "nanvar",
@@ -6612,6 +6613,11 @@ def _apply_support_method_axis_1(self, method, *args, **kwargs):
                 "Row-wise operations currently do not " "support `bool_only`."
             )
 
+        # This parameter is only necessary for axis 0 reductions that cuDF
+        # performs internally. cupy already upcasts smaller integer/bool types
+        # to int64 when accumulating.
+        kwargs.pop("cast_to_int", None)
+
         prepared, mask, common_dtype = self._prepare_for_rowwise_op(
             method, skipna
         )

python/cudf/cudf/tests/test_dataframe.py

@@ -1850,6 +1850,7 @@ def gdf(pdf):
         "min",
         "max",
         "sum",
+        "prod",
         "product",
         "cummin",
         "cummax",
@@ -1872,22 +1873,34 @@ def test_dataframe_reductions(data, axis, func, skipna):
     pdf = pd.DataFrame(data=data)
     gdf = cudf.DataFrame.from_pandas(pdf)
 
-    # These reductions don't support axis=1
-    if axis == 1 and func in ("kurt", "skew"):
-        return
-
-    # We need cupy-supported operations when performing rowwise ops.
-    if func not in cudf.core.dataframe._cupy_nan_methods_map and axis == 1:
-        return
+    # Reductions can fail in numerous possible ways when attempting row-wise
+    # reductions, which are only partially supported. Catching the appropriate
+    # exception here allows us to detect API breakage in the form of changing
+    # exceptions.
+    expected_exception = None
+    if axis == 1:
+        if func in ("kurt", "skew"):
+            expected_exception = NotImplementedError
+        elif func not in cudf.core.dataframe._cupy_nan_methods_map:
+            if skipna is False:
+                expected_exception = NotImplementedError
+            elif any(col.nullable for name, col in gdf.iteritems()):
+                expected_exception = ValueError
+            elif func in ("cummin", "cummax"):
+                expected_exception = AttributeError
 
     # Test different degrees of freedom for var and std.
     all_kwargs = [{"ddof": 1}, {"ddof": 2}] if func in ("var", "std") else [{}]
     for kwargs in all_kwargs:
-        assert_eq(
-            getattr(pdf, func)(axis=axis, skipna=skipna, **kwargs),
-            getattr(gdf, func)(axis=axis, skipna=skipna, **kwargs),
-            check_dtype=False,
-        )
+        if expected_exception is not None:
+            with pytest.raises(expected_exception):
+                getattr(gdf, func)(axis=axis, skipna=skipna, **kwargs),
+        else:
+            assert_eq(
+                getattr(pdf, func)(axis=axis, skipna=skipna, **kwargs),
+                getattr(gdf, func)(axis=axis, skipna=skipna, **kwargs),
+                check_dtype=False,
+            )
 
 
 @pytest.mark.parametrize(