microsoft / hummingbird

Hummingbird compiles trained ML models into tensor computation for faster inference.
MIT License
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SKL 1.5.0 changes #774

Open ksaur opened 1 month ago

ksaur commented 1 month ago

Based on these 2 failures:

Closes #773

ksaur commented 1 month ago

Ok the decomposition bug is definitely fixed!

I am a bit confused about the bagging changes (https://github.com/scikit-learn/scikit-learn/pull/28432) I don't see what would have broken our code. Can you please take a look @interesaaat; I think you know this op best.

=========================== short test summary info ============================
FAILED tests/test_sklearn_bagging.py::TestSklearnBagging::test_bagging_logistic_regression - AssertionError: 
Not equal to tolerance rtol=1e-06, atol=1e-06

Mismatched elements: 200 / 200 (100%)
Max absolute difference: 0.99875297
Max relative difference: 0.99875297
 x: array([[9.809476e-01, 1.905245e-02],
       [9.987530e-01, 1.247026e-03],
       [8.200397e-01, 1.799603e-01],...
 y: array([[0., 1.],
       [0., 1.],
       [0., 1.],...
====== 1 failed, 389 passed, 275 skipped, 59 warnings in 89.85s (0:01:29) ======

It seems that there is some type/rounding issue?