TST use global_random_seed in sklearn/linear_model/tests/test_linear_loss.py #30863
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Hi @sortofamudkip, thanks for your contribution. In order to properly run all tests, can you please push an empty commit inlcuding all the names of the tests that you have changed, like this: This is mentioned in the issue an d needed to run the tests with all the available seeds. |
test_init_zero_coef test_loss_grad_hess_are_the_same test_loss_gradients_hessp_intercept test_gradients_hessians_numerically test_multinomial_coef_shape test_multinomial_hessian_3_classes
test_init_zero_coef test_loss_grad_hess_are_the_same test_loss_gradients_hessp_intercept test_gradients_hessians_numerically test_multinomial_coef_shape test_multinomial_hessian_3_classes
StefanieSenger
approved these changes
Feb 20, 2025
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Thank you @sortofamudkip, it looks all good to me.
I think we can merge this. Would you mind having a look @ogrisel or @betatim? This is from the sprint we had in Berlin yesterday.
adrinjalali
approved these changes
Feb 20, 2025
OmarManzoor
approved these changes
Feb 21, 2025
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Reference Issues/PRs
Towards #22827. All tests passed. @adrinjalali
What does this implement/fix? Explain your changes.
Added
global_random_seedparameter to:test_init_zero_coeftest_loss_grad_hess_are_the_same(passed torandom_X_y_coef)test_loss_gradients_hessp_intercept(passed torandom_X_y_coef)test_gradients_hessians_numerically(passed torandom_X_y_coef)test_multinomial_coef_shape(passed torandom_X_y_coef)test_multinomial_hessian_3_classes(passed torandom_X_y_coef)