Remove deprecations for 25.06

python/cuml/cuml/metrics/_classification.py

@@ -13,8 +13,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
-import warnings
-
 import cudf
 import cupy as cp
 import numpy as np
@@ -59,9 +57,7 @@ def _input_to_cupy_or_cudf_series(x, check_rows=None):
 
 
 @cuml.internals.api_return_any()
-def accuracy_score(
-    y_true, y_pred, *, sample_weight=None, normalize=True, **kwargs
-):
+def accuracy_score(y_true, y_pred, *, sample_weight=None, normalize=True):
     """
     Accuracy classification score.
 
@@ -84,13 +80,6 @@ def accuracy_score(
         classified samples if ``normalize == False``.
     """
 
-    if kwargs:
-        warnings.warn(
-            "`convert_dtype` and `handle` were deprecated from `accuracy_score` "
-            "in version 25.04 and will be removed in 25.06.",
-            FutureWarning,
-        )
-
     y_true = _input_to_cupy_or_cudf_series(y_true)
     y_pred = _input_to_cupy_or_cudf_series(y_pred, check_rows=len(y_true))
 

python/cuml/cuml/metrics/regression.py

@@ -14,8 +14,6 @@
 # limitations under the License.
 #
 
-import warnings
-
 import cupy as cp
 import numpy as np
 
@@ -84,7 +82,6 @@ def r2_score(
     sample_weight=None,
     multioutput="uniform_average",
     force_finite=True,
-    **kwargs,
 ):
     """:math:`R^2` (coefficient of determination) regression score function.
 
@@ -122,13 +119,6 @@ def r2_score(
         The :math:`R^2` score or ndarray of scores if 'multioutput' is
         'raw_values'.
     """
-    if kwargs:
-        warnings.warn(
-            "`convert_dtype` and `handle` were deprecated from `r2_score` in version "
-            "25.02.01 and will be removed in 25.06.",
-            FutureWarning,
-        )
-
     (
         y_true,
         y_pred,

python/cuml/cuml/svm/svc.pyx

@@ -22,8 +22,6 @@ import numpy as np
 from cython.operator cimport dereference as deref
 from libc.stdint cimport uintptr_t
 
-import warnings
-
 import cuml.internals
 from cuml.common.array_descriptor import CumlArrayDescriptor
 from cuml.common.doc_utils import generate_docstring
@@ -335,9 +333,6 @@ class SVC(SVMBase,
         <https://scikit-learn.org/stable/modules/generated/sklearn.multiclass.OneVsOneClassifier.html>`_
         while ``'ovr'`` selects `OneVsRestClassifier
         <https://scikit-learn.org/stable/modules/generated/sklearn.multiclass.OneVsRestClassifier.html>`_
-
-        .. versionadded:: 25.02
-          The parameter `multiclass_strategy` was renamed to `decision_function_shape`.
     nochange_steps : int (default = 1000)
         We monitor how much our stopping criteria changes during outer
         iterations. If it does not change (changes less then 1e-3*tol)
@@ -357,14 +352,6 @@ class SVC(SVMBase,
     verbose : int or boolean, default=False
         Sets logging level. It must be one of `cuml.common.logger.level_*`.
         See :ref:`verbosity-levels` for more info.
-    multiclass_strategy
-        Multiclass classification strategy. ``'ovo'`` uses `OneVsOneClassifier
-        <https://scikit-learn.org/stable/modules/generated/sklearn.multiclass.OneVsOneClassifier.html>`_
-        while ``'ovr'`` selects `OneVsRestClassifier
-        <https://scikit-learn.org/stable/modules/generated/sklearn.multiclass.OneVsRestClassifier.html>`_
-
-        .. versionchanged:: 25.02
-            Renamed to `decision_function_shape`. Will be removed in later versions.
 
     Attributes
     ----------
@@ -421,8 +408,7 @@ class SVC(SVMBase,
                  gamma='scale', coef0=0.0, tol=1e-3, cache_size=1024.0,
                  max_iter=-1, nochange_steps=1000, verbose=False,
                  output_type=None, probability=False, random_state=None,
-                 class_weight=None, decision_function_shape='ovo',
-                 multiclass_strategy="warn"):
+                 class_weight=None, decision_function_shape='ovo'):
         super().__init__(
             handle=handle,
             C=C,
@@ -445,7 +431,6 @@ class SVC(SVMBase,
         self.svmType = C_SVC
 
         self.decision_function_shape = decision_function_shape
-        self.multiclass_strategy = multiclass_strategy
 
     @property
     @cuml.internals.api_base_return_array_skipall
@@ -592,14 +577,6 @@ class SVC(SVMBase,
         Fit the model with X and y.
 
         """
-        if self.multiclass_strategy != "warn":
-            self.decision_function_shape = self.multiclass_strategy
-            warnings.warn(
-                "`multiclass_strategy` was deprecated in 25.04 and will be "
-                "removed in 25.06. Please use `decision_function_shape` instead",
-                FutureWarning
-            )
-
         self.n_classes_ = self._get_num_classes(y)
 
         # we need to check whether input X is sparse
@@ -823,7 +800,7 @@ class SVC(SVMBase,
     @classmethod
     def _get_param_names(cls):
         params = super()._get_param_names() + \
-            ["probability", "random_state", "class_weight", "decision_function_shape", "multiclass_strategy"]
+            ["probability", "random_state", "class_weight", "decision_function_shape"]
 
         # Ignore "epsilon" since its not used in the constructor
         if ("epsilon" in params):