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Ignore warnings caused by sklearn/scipy incompatibility. #7735

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Merged
gforsyth merged 2 commits into from
Jan 29, 2026
Merged

Ignore warnings caused by sklearn/scipy incompatibility. #7735

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6561cca
Ignore warnings caused by sklearn/scipy incompatibility.
csadorf Jan 28, 2026
afc849b
Fix comments.
csadorf Jan 28, 2026
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15 changes: 15 additions & 0 deletions python/cuml/tests/test_linear_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -359,6 +359,11 @@ def test_logistic_regression_unscaled(dtype, l1_ratio, C):
assert score_test >= 0.94


# Ignore scipy 1.17.0+ deprecation warning from sklearn 1.5.x LogisticRegression
# using deprecated L-BFGS-B parameters. This is fixed in sklearn 1.6.0+.
@pytest.mark.filterwarnings(
"ignore:.*The `disp` and `iprint` options.*:DeprecationWarning"
)
@given(dtype=dataset_dtypes())
@example(dtype=np.float32)
@example(dtype=np.float64)
Expand Down Expand Up @@ -570,6 +575,11 @@ def test_logistic_regression_input_type_consistency(constructor, dtype):
assert isinstance(clf.predict(X), expected_type)


# Ignore scipy 1.17.0+ deprecation warning from sklearn 1.5.x LogisticRegression
# using deprecated L-BFGS-B parameters. This is fixed in sklearn 1.6.0+.
@pytest.mark.filterwarnings(
"ignore:.*The `disp` and `iprint` options.*:DeprecationWarning"
)
@pytest.mark.parametrize(
"y_kind", ["object", "fixed-string", "int32", "float32", "float16"]
)
Expand Down Expand Up @@ -759,6 +769,11 @@ def test_logistic_predict_convert_dtype(dataset, test_dtype):
use_sample_weight=False,
class_weight_option=None,
)
# Ignore scipy 1.17.0+ deprecation warning from sklearn 1.5.x LogisticRegression
# using deprecated L-BFGS-B parameters. This is fixed in sklearn 1.6.0+.
@pytest.mark.filterwarnings(
"ignore:.*The `disp` and `iprint` options.*:DeprecationWarning"
)
def test_logistic_regression_weighting(
dataset, use_sample_weight, class_weight_option
):
Expand Down
5 changes: 5 additions & 0 deletions python/cuml/tests/test_sklearn_import_export.py
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Expand Up @@ -213,6 +213,11 @@ def test_linear_regression(random_state):
assert_estimator_roundtrip(original, SkLinearRegression, X, y)


# Ignore scipy 1.17.0+ deprecation warning from sklearn 1.5.x LogisticRegression
# using deprecated L-BFGS-B parameters. This is fixed in sklearn 1.6.0+.
@pytest.mark.filterwarnings(
"ignore:.*The `disp` and `iprint` options.*:DeprecationWarning"
)
def test_logistic_regression(random_state):
X, y = make_classification(
n_samples=50, n_features=5, n_informative=3, random_state=random_state
Expand Down
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