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Flaky e2e test for the XGBoost model with the 'gblinear' booster

See original GitHub issue

Context from @StrikerRUS:

Now Go is failing (refer to https://github.com/BayesWitnesses/m2cgen/pull/200#issuecomment-624063683):

=================================== FAILURES ===================================
_ test_e2e[xgboost_XGBClassifier - go_lang - train_model_classification_binary2] _
estimator = XGBClassifier(base_score=0.6, booster='gblinear', colsample_bylevel=None,
              colsample_bynode=None, colsamp...ambda=0, scale_pos_weight=1, subsample=None,
              tree_method=None, validate_parameters=False, verbosity=None)
executor_cls = <class 'tests.e2e.executors.go.GoExecutor'>

...

expected=[0.04761511 0.9523849 ], actual=[0.047615, 0.952385]
expected=[0.06296992 0.9370301 ], actual=[0.06297, 0.93703]
expected=[0.12447995 0.87552005], actual=[0.124479, 0.875521]
expected=[0.0757848 0.9242152], actual=[0.075784, 0.924216]
expected=[0.8092151  0.19078489], actual=[0.809212, 0.190788]

BTW, in attempts to check my guess from https://github.com/BayesWitnesses/m2cgen/pull/200#issuecomment-624067250, I found that coefs in gblinear are also float32: https://github.com/dmlc/xgboost/blob/67d267f9da3b15a6e5a8393afae9be921a4e224b/src/gbm/gblinear_model.h#L110

https://github.com/dmlc/xgboost/blob/67d267f9da3b15a6e5a8393afae9be921a4e224b/src/gbm/gblinear_model.h#L120

https://github.com/dmlc/xgboost/blob/67d267f9da3b15a6e5a8393afae9be921a4e224b/src/gbm/gblinear_model.h#L82

https://github.com/dmlc/xgboost/blob/67d267f9da3b15a6e5a8393afae9be921a4e224b/src/gbm/gblinear_model.h#L91

and from #188 (comment) we know that bst_float is actually float https://github.com/dmlc/xgboost/blob/8d06878bf9b778db68ae98f68d99a3557c7ea885/include/xgboost/base.h#L110-L111

Created https://github.com/dmlc/xgboost/issues/5634.

Issue Analytics

State:
Created 3 years ago
Comments:6 (6 by maintainers)

Top GitHub Comments

1reaction

StrikerRUScommented, May 6, 2020

I think we can wait for a while for any reply in https://github.com/dmlc/xgboost/issues/5634. Let say two or three days, and only then take any actions.

0reactions

StrikerRUScommented, May 20, 2020

Have no time to read this right now, but looks like related to our issue: https://github.com/numpy/numpy/pull/9941.

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