Improve detection of scikit-learn parity regressions #6553
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…sai#6553) This change modifies the KMeans test to set n_init to 2, enhancing the stability of the k-means|| initialization process. Additional context can be found in issue rapidsai#5530.
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#6555) This change modifies the KMeans test to set n_init to 2, enhancing the stability of the k-means|| initialization process. Additional context can be found in issue #5530. Closes #5530. Authors: - Simon Adorf (https://github.com/csadorf) Approvers: - Divye Gala (https://github.com/divyegala) - Jim Crist-Harif (https://github.com/jcrist) URL: #6555
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- Move most of the related tooling from ci/ to python/cuml/cuml/accel/tests/scikit-learn/ - Add xfail-list.yaml to track known differences from scikit-learn - Add --format=xfail_list to automatically generate xfail lists from failures The infrastructure enables continuous monitoring of scikit-learn parity by: - Running scikit-learn tests with cuML acceleration - Tracking pass rates and comparing against thresholds - Automatically detecting new failures - Managing known differences via xfail lists Import pytest lazily within the pytest_collection_modifyitems function to avoid requiring it for normal cuML usage, ensuring pytest is only needed during test execution.
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This PR enhances the infrastructure for monitoring scikit-learn parity in cuML's accelerated estimators, enabling better tracking and management of differences between scikit-learn and cuML implementations.
Key Changes
ci/topython/cuml/cuml/accel/tests/scikit-learn/for better organizationxfail-list.yamlto track known differences from scikit-learnInfrastructure Capabilities
The new infrastructure enables continuous monitoring of scikit-learn parity by:
Related Changes