How to calculate feature contribution of XGBoost and LightGBM model?

It is able to extract feature contributions of the Random Forest model with the python library "treeinterpreter" with reference to http://blog.datadive.net/random-forest-interpretation-with-scikit-learn/.
Is there a similar way to calculate feature contributions of the XGboost or LightGBM model ? Thank you !

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