Mark a few cuml-accel upstream tests as flaky - #7967
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These tests match based on time in the logs, and can sometimes fail if an operation takes longer (possibly due to CI contention issues).
| - "sklearn.model_selection.tests.test_validation::test_cross_val_predict[coo_matrix]" | ||
| - "sklearn.model_selection.tests.test_validation::test_fit_and_score_verbosity[False-scorer2-10-split_prg2-cdt_prg2-\\\\[CV 2/3; 1/1\\\\] END ....... sc1: \\\\(test=3.421\\\\) sc2: \\\\(test=3.421\\\\) total time= 0.\\\\ds]" | ||
| - "sklearn.model_selection.tests.test_validation::test_fit_and_score_verbosity[False-three_params_scorer-2-split_prg0-cdt_prg0-\\\\[CV\\\\] END .................................................... total time= 0.\\\\ds]" | ||
| - "sklearn.model_selection.tests.test_validation::test_fit_and_score_verbosity[True-scorer1-3-split_prg1-cdt_prg1-\\\\[CV 2/3\\\\] END sc1: \\\\(train=3.421, test=3.421\\\\) sc2: \\\\(train=3.421, test=3.421\\\\) total time= 0.\\\\ds]" |
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I've seen at least one of these fail locally before. That and the fact that test_random_search_cv_results_multimetric was already marked as flaky makes me think this is less of a regression and more of us finally catching (and noting!) a failure for these.
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📝 WalkthroughSummary by CodeRabbit
WalkthroughThe PR extends the xfail list configuration to mark specific flaky scikit-learn tests as expected failures. Four new test entries are added for timing-sensitive tests that fail intermittently in slow CI environments. Changes
Estimated code review effort🎯 1 (Trivial) | ⏱️ ~3 minutes Possibly related issues
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/merge |
These tests match based on time in the logs, and can sometimes fail if an operation takes longer (possibly due to CI contention issues).
Fixes #7962