added extensive comment explaining how to specify tests, and use selectors
+# This file lists node ids (in pytest sense) of sklearn tests that
+# are to be deselected during test discovery step.
+#
+# Deselection can be predicated on the version of scikit-learn used.
+# Use - node_id cond, or - node_id cond1,cond2 where cond is OPver.
+# Supported OPs are >=, <=, ==, !=, >, <
+# For example,
+# - tests/test_isotonic.py::test_permutation_invariance >0.18,<=0.19
+# will exclude deselection in versions 0.18.1, and 0.18.2 only
+
deselected_tests:
+
# Deselecting 5 SVC related tests where duplicate samples end up being support vectors
# See: https://github.com/scikit-learn/scikit-learn/issues/12738
- svm/tests/test_svm.py::test_sample_weights
@@ -6,9 +17,11 @@ deselected_tests:
- svm/tests/test_sparse.py::test_sparse
- svm/tests/test_sparse.py::test_svc_iris
- ensemble/tests/test_bagging.py::test_sparse_classification
+
# test_k_means_fit_predict is known to sporadically fail for float32 inputs in multithreaded runs
# See: https://github.com/IntelPython/daal4py/issues/25
- cluster/tests/test_k_means.py::test_k_means_fit_predict
+
# test_non_uniform_strategies fails due to differences in handling of vacuous clusters after update
# See https://github.com/IntelPython/daal4py/issues/69
- preprocessing/tests/test_discretization.py::test_nonuniform_strategies >=0.20.3
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