Update deselected_tests.yaml

intel · Nov 12, 2024 · 7bdb533 · 7bdb533
1 parent 660aaf1
commit 7bdb533
Showing 1 changed file with 47 additions and 47 deletions.
diff --git a/deselected_tests.yaml b/deselected_tests.yaml
@@ -381,25 +381,25 @@ gpu:
   # Segfaults
   - ensemble/tests/test_weight_boosting.py
   # Fails
-  #- cluster/tests/test_dbscan.py::test_weighted_dbscan
-  #- cluster/tests/test_k_means.py::test_kmeans_elkan_results[42-1e-100-sparse-normal]
-  #- model_selection/tests/test_search.py::test_unsupervised_grid_search
-  #- ensemble/tests/test_bagging.py::test_estimators_samples
-  #- ensemble/tests/test_voting.py::test_sample_weight
-  #- metrics/tests/test_score_objects.py::test_average_precision_pos_label
-  #- model_selection/tests/test_search.py::test_search_default_iid
-  #- neighbors/tests/test_neighbors.py::test_unsupervised_kneighbors
-  #- neighbors/tests/test_neighbors.py::test_neighbors_metrics
-  #- svm/tests/test_sparse.py::test_svc
-  #- svm/tests/test_sparse.py::test_svc_iris
-  #- svm/tests/test_sparse.py::test_sparse_realdata
-  #- svm/tests/test_svm.py::test_precomputed
-  #- svm/tests/test_svm.py::test_tweak_params
-  #- svm/tests/test_svm.py::test_svm_classifier_sided_sample_weight[estimator0]
-  #- svm/tests/test_svm.py::test_svm_equivalence_sample_weight_C
-  #- svm/tests/test_svm.py::test_negative_weights_svc_leave_two_labels[partial-mask-label-1-SVC]
-  #- svm/tests/test_svm.py::test_negative_weights_svc_leave_two_labels[partial-mask-label-2-SVC]
-  #- svm/tests/test_svm.py::test_svc_clone_with_callable_kernel
+  - cluster/tests/test_dbscan.py::test_weighted_dbscan
+  - cluster/tests/test_k_means.py::test_kmeans_elkan_results[42-1e-100-sparse-normal]
+  - model_selection/tests/test_search.py::test_unsupervised_grid_search
+  - ensemble/tests/test_bagging.py::test_estimators_samples
+  - ensemble/tests/test_voting.py::test_sample_weight
+  - metrics/tests/test_score_objects.py::test_average_precision_pos_label
+  - model_selection/tests/test_search.py::test_search_default_iid
+  - neighbors/tests/test_neighbors.py::test_unsupervised_kneighbors
+  - neighbors/tests/test_neighbors.py::test_neighbors_metrics
+  - svm/tests/test_sparse.py::test_svc
+  - svm/tests/test_sparse.py::test_svc_iris
+  - svm/tests/test_sparse.py::test_sparse_realdata
+  - svm/tests/test_svm.py::test_precomputed
+  - svm/tests/test_svm.py::test_tweak_params
+  - svm/tests/test_svm.py::test_svm_classifier_sided_sample_weight[estimator0]
+  - svm/tests/test_svm.py::test_svm_equivalence_sample_weight_C
+  - svm/tests/test_svm.py::test_negative_weights_svc_leave_two_labels[partial-mask-label-1-SVC]
+  - svm/tests/test_svm.py::test_negative_weights_svc_leave_two_labels[partial-mask-label-2-SVC]
+  - svm/tests/test_svm.py::test_svc_clone_with_callable_kernel
   # sparse input is not implemented for DBSCAN.
   - tests/test_common.py::test_estimators[RandomForestClassifier()-check_class_weight_classifiers]
   - tests/test_common.py::test_estimators[SVC()-check_sample_weights_not_an_array]
@@ -412,26 +412,26 @@ gpu:
   - tests/test_common.py::test_search_cv
 
   # Other device issues
-  #- tests/test_multioutput.py::test_classifier_chain_tuple_order[list]
-  #- tests/test_multioutput.py::test_classifier_chain_tuple_order[tuple]
+  - tests/test_multioutput.py::test_classifier_chain_tuple_order[list]
+  - tests/test_multioutput.py::test_classifier_chain_tuple_order[tuple]
   # KD Tree (not implemented for GPU)
   - neighbors/tests/test_neighbors.py::test_neigh_predictions_algorithm_agnosticity[float64-KNeighborsClassifier-50-500-l2-1000-5-100]
   - neighbors/tests/test_neighbors.py::test_neigh_predictions_algorithm_agnosticity[float64-KNeighborsClassifier-100-1000-l2-1000-5-100]
   - neighbors/tests/test_neighbors.py::test_neigh_predictions_algorithm_agnosticity[float64-KNeighborsRegressor-50-500-l2-1000-5-100]
   - neighbors/tests/test_neighbors.py::test_neigh_predictions_algorithm_agnosticity[float64-KNeighborsRegressor-100-1000-l2-1000-5-100]
   # failing due to numeric/code error
-  #- linear_model/tests/test_common.py::test_balance_property[42-False-LogisticRegressionCV]
-  #- sklearn/manifold/tests/test_t_sne.py::test_n_iter_without_progress
-  #- model_selection/tests/test_search.py::test_searchcv_raise_warning_with_non_finite_score[RandomizedSearchCV-specialized_params1-False]
-  #- model_selection/tests/test_search.py::test_searchcv_raise_warning_with_non_finite_score[RandomizedSearchCV-specialized_params1-True]
-  #- tests/test_calibration.py::test_calibrated_classifier_cv_double_sample_weights_equivalence
-  #- tests/test_calibration.py::test_calibrated_classifier_cv_zeros_sample_weights_equivalence
-  #- tests/test_common.py::test_estimators[FeatureAgglomeration()-check_parameters_default_constructible]
-  #- neighbors/tests/test_lof.py::test_novelty_true_common_tests[LocalOutlierFactor(novelty=True)-check_methods_subset_invariance]
-  #- tests/test_common.py::test_transformers_get_feature_names_out[StackingRegressor(estimators=[('est1',Ridge(alpha=0.1)),('est2',Ridge(alpha=1))])]
-  #- tests/test_common.py::test_transformers_get_feature_names_out[VotingRegressor(estimators=[('est1',Ridge(alpha=0.1)),('est2',Ridge(alpha=1))])]
-  #- tests/test_common.py::test_f_contiguous_array_estimator[TSNE]
-  #- manifold/tests/test_t_sne.py::test_tsne_works_with_pandas_output
+  - linear_model/tests/test_common.py::test_balance_property[42-False-LogisticRegressionCV]
+  - sklearn/manifold/tests/test_t_sne.py::test_n_iter_without_progress
+  - model_selection/tests/test_search.py::test_searchcv_raise_warning_with_non_finite_score[RandomizedSearchCV-specialized_params1-False]
+  - model_selection/tests/test_search.py::test_searchcv_raise_warning_with_non_finite_score[RandomizedSearchCV-specialized_params1-True]
+  - tests/test_calibration.py::test_calibrated_classifier_cv_double_sample_weights_equivalence
+  - tests/test_calibration.py::test_calibrated_classifier_cv_zeros_sample_weights_equivalence
+  - tests/test_common.py::test_estimators[FeatureAgglomeration()-check_parameters_default_constructible]
+  - neighbors/tests/test_lof.py::test_novelty_true_common_tests[LocalOutlierFactor(novelty=True)-check_methods_subset_invariance]
+  - tests/test_common.py::test_transformers_get_feature_names_out[StackingRegressor(estimators=[('est1',Ridge(alpha=0.1)),('est2',Ridge(alpha=1))])]
+  - tests/test_common.py::test_transformers_get_feature_names_out[VotingRegressor(estimators=[('est1',Ridge(alpha=0.1)),('est2',Ridge(alpha=1))])]
+  - tests/test_common.py::test_f_contiguous_array_estimator[TSNE]
+  - manifold/tests/test_t_sne.py::test_tsne_works_with_pandas_output
 
   # GPU Forest algorithm implementation does not follow certain Scikit-learn standards
   - ensemble/tests/test_forest.py::test_max_leaf_nodes_max_depth
@@ -441,17 +441,17 @@ gpu:
   - ensemble/tests/test_forest.py::test_max_samples_boundary_regressors
 
   # numerical issues in GPU Forest algorithms which require further investigation
-  #- ensemble/tests/test_voting.py::test_predict_on_toy_problem[42]
-  #- tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_class_weight_classifiers]
-  #- tests/test_common.py::test_estimators[ExtraTreesRegressor()-check_sample_weights_invariance(kind=zeros)]
-  #- tests/test_common.py::test_estimators[RandomForestRegressor()-check_regressor_data_not_an_array]
-  #- ensemble/tests/test_forest.py::test_max_samples_boundary_classifiers[ExtraTreesClassifier]
-  #- tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_classifier_data_not_an_array]
-  #- tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_classifiers_train]
-  #- tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_classifiers_train(readonly_memmap=True)]
-  #- tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_fit_idempotent]
-  #- tests/test_common.py::test_estimators[ExtraTreesRegressor()-check_fit_idempotent]
-  #- tests/test_common.py::test_estimators[ExtraTreesRegressor()-check_regressor_data_not_an_array]
+  - ensemble/tests/test_voting.py::test_predict_on_toy_problem[42]
+  - tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_class_weight_classifiers]
+  - tests/test_common.py::test_estimators[ExtraTreesRegressor()-check_sample_weights_invariance(kind=zeros)]
+  - tests/test_common.py::test_estimators[RandomForestRegressor()-check_regressor_data_not_an_array]
+  - ensemble/tests/test_forest.py::test_max_samples_boundary_classifiers[ExtraTreesClassifier]
+  - tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_classifier_data_not_an_array]
+  - tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_classifiers_train]
+  - tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_classifiers_train(readonly_memmap=True)]
+  - tests/test_common.py::test_estimators[ExtraTreesClassifier()-check_fit_idempotent]
+  - tests/test_common.py::test_estimators[ExtraTreesRegressor()-check_fit_idempotent]
+  - tests/test_common.py::test_estimators[ExtraTreesRegressor()-check_regressor_data_not_an_array]
 
   # GPU implementation of Extra Trees doesn't support sample_weights
   # comparisons to GPU with sample weights will use different algorithms
@@ -460,10 +460,10 @@ gpu:
   - tests/test_common.py::test_estimators[ExtraTreesRegressor()-check_sample_weights_invariance(kind=ones)]
 
   # RuntimeError: Device support is not implemented, failing as result of fallback to cpu false
-  #- svm/tests/test_svm.py::test_unfitted
-  #- tests/test_common.py::test_estimators[SVC()-check_estimators_unfitted]
+  - svm/tests/test_svm.py::test_unfitted
+  - tests/test_common.py::test_estimators[SVC()-check_estimators_unfitted]
 
   # Failed on the onedal's LinearRegression call.
   # RuntimeError: oneapi::mkl::lapack::potrf: computation error: info = 2: Leading principal minor of order
   # 2 is not positive, and the factorization could not be completed.
-  #- ensemble/tests/test_stacking.py::test_stacking_prefit[StackingRegressor-DummyRegressor-predict-final_estimator1-X1-y1]
+  - ensemble/tests/test_stacking.py::test_stacking_prefit[StackingRegressor-DummyRegressor-predict-final_estimator1-X1-y1]