TST use global_random_seed in sklearn/linear_model/tests/test_logistic.py
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@DeaMariaLeon Please note that |
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Thank you so much @lorentzenchr! |
DeaMariaLeon
commented
May 20, 2025
| @@ -254,13 +253,16 @@ def test_elasticnet_l1_ratio_err_helpful(LR): | |||
| # TODO(1.8): remove whole test with deprecation of multi_class | |||
| @pytest.mark.filterwarnings("ignore:.*'multi_class' was deprecated.*:FutureWarning") | |||
| @pytest.mark.parametrize("solver", ["lbfgs", "newton-cg", "sag", "saga"]) | |||
| def test_multinomial_binary(solver): | |||
| def test_multinomial_binary(global_random_seed, solver): | |||
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Maybe this test doesn't need global_random_seed as it will be removed
DeaMariaLeon
commented
May 20, 2025
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| params = dict(fit_intercept=False, random_state=42) | ||
| params = dict(C=0.1, fit_intercept=False, random_state=global_random_seed) |
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Is it better to skip the solvers that don't use random_state, but make the code a bit more complex with the skip? or to add global_random_seed to all the solvers but make the test take longer?
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Reference Issues/PRs
Towards #22827
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