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Merged
rapids-bot merged 3 commits into from
May 19, 2026
Merged

A few fixes for sklearn 1.9 pre-release #8126

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36958e5
A few fixes for sklearn 1.9 pre-release
jcrist May 18, 2026
eaedf26
Respond to feedback
jcrist May 18, 2026
a0b51dc
Merge branch 'release/26.06' into fix-sklearn-19-nightly
jcrist May 19, 2026
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8 changes: 4 additions & 4 deletions python/cuml/cuml/accel/_overrides/sklearn/preprocessing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,13 +76,13 @@ def _check_targetencoder_y(y):
class TargetEncoder(ProxyBase):
_gpu_class = cuml.preprocessing.TargetEncoder

def _gpu_fit(self, X, y, **kwargs):
def _gpu_fit(self, X, y):
_check_targetencoder_y(y)
return self._gpu.fit(X, y, **kwargs)
return self._gpu.fit(X, y)

def _gpu_fit_transform(self, X, y, **kwargs):
def _gpu_fit_transform(self, X, y, **params):
_check_targetencoder_y(y)
return self._gpu.fit_transform(X, y, **kwargs)
return self._gpu.fit_transform(X, y, **params)
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def _gpu_get_feature_names_out(self, input_features=None):
"""Return feature names for output features.
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6 changes: 6 additions & 0 deletions python/cuml/cuml_accel_tests/integration/test_svc.py
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Expand Up @@ -37,6 +37,12 @@ def test_svc(binary):
assert svc.score(X, y) > 0.5


@pytest.mark.filterwarnings(
"ignore:The `probability` parameter was deprecated:FutureWarning"
)
@pytest.mark.filterwarnings(
"ignore:Attribute `prob[AB]_` was deprecated:FutureWarning"
)
def test_svc_probability(binary):
X, y = binary
svc = SVC(probability=True).fit(X, y)
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14 changes: 12 additions & 2 deletions python/cuml/cuml_accel_tests/integration/test_tsvd.py
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Original file line number Diff line number Diff line change
@@ -1,10 +1,12 @@
#
# SPDX-FileCopyrightText: Copyright (c) 2024-2025, NVIDIA CORPORATION.
# SPDX-FileCopyrightText: Copyright (c) 2024-2026, NVIDIA CORPORATION.
# SPDX-License-Identifier: Apache-2.0
#

import numpy as np
import pytest
import sklearn
from packaging.version import Version
from scipy.sparse import csr_matrix
from sklearn.datasets import make_classification
from sklearn.decomposition import TruncatedSVD
Expand Down Expand Up @@ -100,11 +102,19 @@ def test_truncated_svd_tol(svd_data, tol):


@pytest.mark.parametrize(
"power_iteration_normalizer", ["auto", "OR", "LU", "none"]
"power_iteration_normalizer", ["auto", "QR", "LU", "none"]
)
def test_truncated_svd_power_iteration_normalizer(
svd_data, power_iteration_normalizer
):
if (
Version(sklearn.__version__) < Version("1.9.0.dev0")
and power_iteration_normalizer == "QR"
):
pytest.skip(
"power_iteration_normalizer 'QR' is not supported in scikit-learn < 1.9.0"
)

X, _ = svd_data
svd = TruncatedSVD(
n_components=10,
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5 changes: 0 additions & 5 deletions python/cuml/tests/test_sklearn_compatibility.py
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Expand Up @@ -208,7 +208,6 @@
},
KernelDensity: {
"check_estimator_tags_renamed": "No support for modern tags infrastructure",
"check_all_zero_sample_weights_error": "KernelDensity does not validate all-zero sample weights",
},
EmpiricalCovariance: {
"check_estimator_tags_renamed": "No support for modern tags infrastructure",
Expand Down Expand Up @@ -247,7 +246,6 @@
"check_sample_weights_not_an_array": "sample_weight not implemented",
"check_sample_weights_shape": "sample_weight not implemented",
"check_sample_weight_equivalence_on_dense_data": "sample_weight not implemented",
"check_all_zero_sample_weights_error": "sample_weight not implemented",
"check_sample_weights_list": "sample_weight not implemented",
"check_sample_weights_not_overwritten": "sample_weight not implemented",
"check_sample_weight_equivalence_on_sparse_data": "sample_weight not implemented",
Expand All @@ -260,7 +258,6 @@
"check_sample_weights_not_an_array": "sample_weight not implemented",
"check_sample_weights_shape": "sample_weight not implemented",
"check_sample_weight_equivalence_on_dense_data": "sample_weight not implemented",
"check_all_zero_sample_weights_error": "sample_weight not implemented",
"check_sample_weights_list": "sample_weight not implemented",
"check_sample_weights_not_overwritten": "sample_weight not implemented",
"check_sample_weight_equivalence_on_sparse_data": "sample_weight not implemented",
Expand All @@ -273,7 +270,6 @@
"check_sample_weights_not_an_array": "sample_weight not implemented",
"check_sample_weights_shape": "sample_weight not implemented",
"check_sample_weight_equivalence_on_dense_data": "sample_weight not implemented",
"check_all_zero_sample_weights_error": "sample_weight not implemented",
"check_sample_weights_list": "sample_weight not implemented",
"check_sample_weights_not_overwritten": "sample_weight not implemented",
"check_sample_weight_equivalence_on_sparse_data": "sample_weight not implemented",
Expand All @@ -286,7 +282,6 @@
"check_sample_weights_not_an_array": "sample_weight not implemented",
"check_sample_weights_shape": "sample_weight not implemented",
"check_sample_weight_equivalence_on_dense_data": "sample_weight not implemented",
"check_all_zero_sample_weights_error": "sample_weight not implemented",
"check_sample_weights_list": "sample_weight not implemented",
"check_sample_weights_not_overwritten": "sample_weight not implemented",
"check_sample_weight_equivalence_on_sparse_data": "sample_weight not implemented",
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3 changes: 3 additions & 0 deletions python/cuml/tests/test_sklearn_import_export.py
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Expand Up @@ -379,6 +379,9 @@ def test_svr(random_state, sparse, kernel):
@pytest.mark.filterwarnings(
"ignore:The `probability` parameter was deprecated:FutureWarning"
)
@pytest.mark.filterwarnings(
"ignore:Attribute `prob[AB]_` was deprecated:FutureWarning"
)
@pytest.mark.parametrize("sparse", [False, True])
@pytest.mark.parametrize("probability", [False, True])
@pytest.mark.parametrize("kernel", ["rbf", "precomputed"])
Expand Down
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