Handle cupy array in Dataframe.__setitem__ (#7340)

Fixes: #7337 

This PR introduces changes to handle `cupy` array in `DataFrame.__setitem__`.

Authors:
  - GALI PREM SAGAR (@galipremsagar)

Approvers:
  - Ashwin Srinath (@shwina)

URL: #7340

python/cudf/cudf/core/dataframe.py

@@ -39,6 +39,7 @@
 from cudf.utils import applyutils, docutils, ioutils, queryutils, utils
 from cudf.utils.docutils import copy_docstring
 from cudf.utils.dtypes import (
+    can_convert_to_column,
     cudf_dtype_from_pydata_dtype,
     find_common_type,
     is_categorical_dtype,
@@ -683,20 +684,9 @@ def __getitem__(self, arg):
         elif isinstance(arg, slice):
             return self._slice(arg)
 
-        elif isinstance(
-            arg,
-            (
-                list,
-                cupy.ndarray,
-                np.ndarray,
-                pd.Series,
-                Series,
-                Index,
-                pd.Index,
-            ),
-        ):
+        elif can_convert_to_column(arg):
             mask = arg
-            if isinstance(mask, list):
+            if is_list_like(mask):
                 mask = pd.Series(mask)
             if mask.dtype == "bool":
                 return self._apply_boolean_mask(mask)
@@ -776,11 +766,9 @@ def __setitem__(self, arg, value):
                     # pandas raises key error here
                     self.insert(len(self._data), arg, value)
 
-        elif isinstance(
-            arg, (list, np.ndarray, pd.Series, Series, Index, pd.Index)
-        ):
+        elif can_convert_to_column(arg):
             mask = arg
-            if isinstance(mask, list):
+            if is_list_like(mask):
                 mask = np.array(mask)
 
             if mask.dtype == "bool":

python/cudf/cudf/tests/test_dataframe.py

@@ -8315,3 +8315,15 @@ def test_dataframe_roundtrip_arrow_struct_dtype(gdf):
     expected = gd.DataFrame.from_arrow(table)
 
     assert_eq(gdf, expected)
+
+
+def test_dataframe_setitem_cupy_array():
+    np.random.seed(0)
+    pdf = pd.DataFrame(np.random.randn(10, 2))
+    gdf = gd.from_pandas(pdf)
+
+    gpu_array = cupy.array([True, False] * 5)
+    pdf[gpu_array.get()] = 1.5
+    gdf[gpu_array] = 1.5
+
+    assert_eq(pdf, gdf)