incompatible with XGBoost 1.5.0 due to breaking model format changes

In xgboost 1.5.0 release, a breaking change is introduced to the model format causing this error when trying to use convert:

ValueError: invalid literal for int() with base 10: '<some_feature_name>'

The error happens because this line: https://github.com/microsoft/hummingbird/blob/main/hummingbird/ml/operator_converters/xgb.py#L33

Previously, XGBoost seemed to use an indexed integer to store the feature name, but now it’s changed to the alphabet name of the feature. I tried changing the conversion to use other bases, say 36 to get some 1-1 integer map to the feature name, but is causing another issue down the road in the indexing. Seemed like the lib may need to build some indexing to the feature.

Dataset used: sklearn.datasets.load_boston

[interesaaat]

Still we will try to fix the pandas problem for training because it is not that convenient to force users to use numpy for training xgboost models.

[meta]

sure, here’s the repro notebook: https://github.com/meta/notebooks/blob/main/hummingbird_xgboost.ipynb