TST Fix CI: mark check_all_zero_sample_weights_error as expected failure - #101
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scikit-learn's check_all_zero_sample_weights_error expects fit to raise a ValueError when all sample weights are zero. himalaya intentionally allows fitting with all-zero sample weights (see test_kernel_ridge_sample_weight_basic), so the kernel estimators fail this check under newer scikit-learn versions (observed on Python 3.11/3.12 in CI). Add the check to expected_failed_checks for all kernel estimators so it is reported as a documented xfail rather than a CI failure.
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This pull request updates the expected_failed_checks function in himalaya/kernel_ridge/tests/test_sklearn_api_kernel.py to include check_all_zero_sample_weights_error as an expected failed check for all estimators. This is because himalaya intentionally allows fitting with all-zero sample weights instead of raising a ValueError. There are no review comments, so I have no feedback to provide.
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Summary
The
run-testsjobs on Python 3.11 and 3.12 (e.g. on #100) fail with 8 errors, all of the form:These failures are unrelated to the codecov-action bump in #100 — they are pre-existing on
mainand only surface on Python 3.11/3.12 because those jobs install a newer scikit-learn (≥1.6) that added thecheck_all_zero_sample_weights_errorestimator check.That check expects
fitto raise aValueErrorwhen all sample weights are zero. himalaya intentionally allows fitting with all-zero sample weights — seetest_kernel_ridge_sample_weight_basic, which explicitly asserts that this does not raise. So rather than changing estimator behavior, this marks the check as a documented expected failure via the existingexpected_failed_checksmechanism (sklearn ≥1.6's replacement for_xfail_checks).Changes
expected_failed_checksintest_sklearn_api_kernel.pyto markcheck_all_zero_sample_weights_erroras an expected failure for all four kernel estimators (KernelRidge_,KernelRidgeCV_,MultipleKernelRidgeCV_,WeightedKernelRidge_).The ridge estimators don't need this — scikit-learn does not generate that check for them.
Verification
Reproduced the 8 failures locally with scikit-learn 1.9.0, then confirmed they become clean
xfails after the change. The full numpy-backendtest_check_estimatorsuite passes with no failures.🤖 Generated with Claude Code
Generated by Claude Code