Fix loc/iloc.__setitem__[:, loc] with non cupy types (#16677)

Discovered in #16652, `DataFrame.iloc/loc.__setitem__` with a non-cupy type e.g. `"category"` failed because the indexing path unconditionally tries to `cupy.asarray` the value to be set which only accepts types recognized by cupy.

We can skip this `asarray` if we have a numpy/pandas/cudf object

Authors:
  - Matthew Roeschke (https://github.com/mroeschke)

Approvers:
  - GALI PREM SAGAR (https://github.com/galipremsagar)

URL: #16677

python/cudf/cudf/core/dataframe.py

@@ -414,8 +414,9 @@ def _setitem_tuple_arg(self, key, value):
                     )
 
             else:
-                value = cupy.asarray(value)
-                if value.ndim == 2:
+                if not is_column_like(value):
+                    value = cupy.asarray(value)
+                if getattr(value, "ndim", 1) == 2:
                     # If the inner dimension is 1, it's broadcastable to
                     # all columns of the dataframe.
                     indexed_shape = columns_df.loc[key[0]].shape
@@ -558,8 +559,9 @@ def _setitem_tuple_arg(self, key, value):
         else:
             # TODO: consolidate code path with identical counterpart
             # in `_DataFrameLocIndexer._setitem_tuple_arg`
-            value = cupy.asarray(value)
-            if value.ndim == 2:
+            if not is_column_like(value):
+                value = cupy.asarray(value)
+            if getattr(value, "ndim", 1) == 2:
                 indexed_shape = columns_df.iloc[key[0]].shape
                 if value.shape[1] == 1:
                     if value.shape[0] != indexed_shape[0]:

python/cudf/cudf/tests/test_indexing.py

@@ -2369,3 +2369,13 @@ def test_duplicate_labels_raises():
         df[["a", "a"]]
     with pytest.raises(ValueError):
         df.loc[:, ["a", "a"]]
+
+
+@pytest.mark.parametrize("indexer", ["iloc", "loc"])
+@pytest.mark.parametrize("dtype", ["category", "timedelta64[ns]"])
+def test_loc_iloc_setitem_col_slice_non_cupy_types(indexer, dtype):
+    df_pd = pd.DataFrame(range(2), dtype=dtype)
+    df_cudf = cudf.DataFrame.from_pandas(df_pd)
+    getattr(df_pd, indexer)[:, 0] = getattr(df_pd, indexer)[:, 0]
+    getattr(df_cudf, indexer)[:, 0] = getattr(df_cudf, indexer)[:, 0]
+    assert_eq(df_pd, df_cudf)