Fix svm for scikit-learn 1.0.1 (#837)

Author: Pahandrovich

.ci/pipeline/release.yml

@@ -16,7 +16,7 @@
 
 variables:
   DESCRIPTION: ReleaseTesting
-  DESELECT: --deselect ::test_svc_clone_with_callable_kernel --deselect ::test_precomputed --deselect ::test_tweak_params --deselect ::test_probability --deselect ::test_custom_kernel_not_array_input --deselect ::test_unicode_kernel --deselect ::test_consistent_proba
+  DESELECT: --deselect ::test_svc_clone_with_callable_kernel --deselect ::test_precomputed --deselect ::test_tweak_params --deselect ::test_probability --deselect ::test_custom_kernel_not_array_input --deselect ::test_unicode_kernel --deselect ::test_consistent_proba --deselect ::test_svc_raises_error_internal_representation
   TEST_COMMAND: python -m sklearnex -m pytest -ra --disable-warnings --pyargs sklearn.svm.tests.test_svm $(DESELECT)
 
 jobs:

onedal/svm/svm.py

@@ -247,6 +247,12 @@ def _predict(self, X, module, queue):
             raise ValueError("break_ties must be False when "
                              "decision_function_shape is 'ovo'")
 
+        if (module in [_backend.svm.classification, _backend.svm.nu_classification]):
+            sv = self.support_vectors_
+            if not self._sparse and sv.size > 0 and self._n_support.sum() != sv.shape[0]:
+                raise ValueError("The internal representation "
+                                 f"of {self.__class__.__name__} was altered")
+
         if self.break_ties and self.decision_function_shape == 'ovr' and \
                 len(self.classes_) > 2:
             y = np.argmax(self.decision_function(X), axis=1)
@@ -310,6 +316,12 @@ def _decision_function(self, X, module, queue):
                 "cannot use sparse input in %r trained on dense data"
                 % type(self).__name__)
 
+        if (module in [_backend.svm.classification, _backend.svm.nu_classification]):
+            sv = self.support_vectors_
+            if not self._sparse and sv.size > 0 and self._n_support.sum() != sv.shape[0]:
+                raise ValueError("The internal representation "
+                                 f"of {self.__class__.__name__} was altered")
+
         policy = _get_policy(queue, X)
         params = self._get_onedal_params(X)