Remove xfailed cudf pandas tests

python/cuml/tests/test_doctest.py

@@ -9,19 +9,11 @@
 import warnings
 
 import cudf
-import cudf.pandas
 import numpy as np
 import pytest
 
 import cuml
 
-cudf_pandas_active = cudf.pandas.LOADED
-
-_XFAIL_CUDF_PANDAS_21695 = pytest.mark.xfail(
-    reason="rapidsai/cudf#21695: cudf.Series.astype(str) raises TypeError under cudf.pandas",
-    strict=True,
-)
-
 
 def _name_in_all(parent, name):
     return name in getattr(parent, "__all__", [])
@@ -87,17 +79,9 @@ def _find_doctests_in_obj(obj, finder=None, criteria=None):
             yield from _find_doctests_in_obj(member, finder)
 
 
-def _doctest_params():
-    for docstring in _find_doctests_in_obj(cuml):
-        if docstring.name == "LabelEncoder" and cudf_pandas_active:
-            yield pytest.param(docstring, marks=_XFAIL_CUDF_PANDAS_21695)
-        else:
-            yield docstring
-
-
 @pytest.mark.parametrize(
     "docstring",
-    _doctest_params(),
+    _find_doctests_in_obj(cuml),
     ids=lambda docstring: docstring.name,
 )
 def test_docstring(docstring):

python/cuml/tests/test_label_encoder.py

@@ -2,7 +2,6 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import cudf
-import cudf.pandas
 import cupy as cp
 import numpy as np
 import pandas as pd
@@ -12,8 +11,6 @@
 
 from cuml.preprocessing.LabelEncoder import LabelEncoder
 
-cudf_pandas_active = cudf.pandas.LOADED
-
 
 def _df_to_similarity_mat(df):
     arr = df.to_numpy().reshape(1, -1)
@@ -77,11 +74,6 @@ def test_labelencoder_unfitted():
         le.transform(df)
 
 
-@pytest.mark.xfail(
-    cudf_pandas_active,
-    reason="rapidsai/cudf#21695: cudf.Series.astype(str) raises TypeError under cudf.pandas",
-    strict=True,
-)
 @pytest.mark.parametrize("use_fit_transform", [False, True])
 @pytest.mark.parametrize(
     "orig_label, ord_label, expected_reverted, bad_ord_label",

python/cuml/tests/test_one_hot_encoder.py

@@ -2,7 +2,6 @@
 # SPDX-License-Identifier: Apache-2.0
 import math
 
-import cudf.pandas
 import cupy as cp
 import numpy as np
 import pandas as pd
@@ -18,8 +17,6 @@
     stress_param,
 )
 
-cudf_pandas_active = cudf.pandas.LOADED
-
 
 def _from_df_to_cupy(df):
     """Transform char columns to integer columns, and then create an array"""
@@ -170,17 +167,7 @@ def test_onehot_random_inputs(drop, sparse, n_samples, as_array):
 
 @pytest.mark.parametrize(
     "as_array",
-    [
-        True,
-        pytest.param(
-            False,
-            marks=pytest.mark.xfail(
-                condition=cudf_pandas_active,
-                reason="rapidsai/cudf#21695: cudf.Series.astype(str) raises TypeError under cudf.pandas",
-                strict=True,
-            ),
-        ),
-    ],
+    [True, False],
     ids=["cupy", "cudf"],
 )
 def test_onehot_drop_idx_first(as_array):
@@ -203,17 +190,7 @@ def test_onehot_drop_idx_first(as_array):
 
 @pytest.mark.parametrize(
     "as_array",
-    [
-        True,
-        pytest.param(
-            False,
-            marks=pytest.mark.xfail(
-                condition=cudf_pandas_active,
-                reason="rapidsai/cudf#21695: cudf.Series.astype(str) raises TypeError under cudf.pandas",
-                strict=True,
-            ),
-        ),
-    ],
+    [True, False],
     ids=["cupy", "cudf"],
 )
 def test_onehot_drop_one_of_each(as_array):

python/cuml/tests/test_ordinal_encoder.py

@@ -1,6 +1,5 @@
 # SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
 # SPDX-License-Identifier: Apache-2.0
-import cudf.pandas
 import cupy as cp
 import numpy as np
 import pandas as pd
@@ -10,20 +9,13 @@
 
 from cuml.preprocessing import OrdinalEncoder
 
-cudf_pandas_active = cudf.pandas.LOADED
-
 
 @pytest.fixture
 def test_sample():
     X = DataFrame({"cat": ["M", "F", "F"], "num": [1, 3, 2]})
     return X
 
 
-@pytest.mark.xfail(
-    cudf_pandas_active,
-    reason="rapidsai/cudf#21695: cudf.Series.astype(str) raises TypeError under cudf.pandas",
-    strict=True,
-)
 def test_ordinal_encoder_df(test_sample) -> None:
     X = test_sample
     enc = OrdinalEncoder()