TODO: make 1.0 release #111
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This was referenced Sep 10, 2019
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Hi~ I wonder when will 1.0 version release? I await the new version:) |
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See #130 |
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This was referenced Sep 25, 2020
hcho3
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Oct 9, 2020
Addresses #95 and #111. Follow-up to #198, #199, #201 Trying again, since #130 failed. This time, I made the Model class to be polymorphic. This way, the amount of pointer indirection is minimized. Summary: Model is an opaque container that wraps the polymorphic handle ModelImpl<ThresholdType, LeafOutputType>. The handle in turn stores the list of trees Tree<ThresholdType, LeafOutputType>. To unbox the Model container and obtain ModelImpl<ThresholdType, LeafOutputType>, use Model::Dispatch(<lambda expression>). Also, upgrade to C++14 to access the generic lambda feature, which proved to be very useful in the dispatching logic for the polymorphic Model class. * Turn the Model and Tree classes into template classes * Revise the string templates so that correct data types are used in the generated C code * Rewrite the model builder class * Revise the zero-copy serializer * Create an abstract matrix class that supports multiple data types (float32, float64 for now). * Move the DMatrix class to the runtime. * Extend the DMatrix class so that it can hold float32 and float64. * Redesign the C runtime API using the DMatrix class. * Ensure accuracy of scikit-learn models. To achieve the best results, use float32 for the input matrix and float64 for the split thresholds and leaf outputs. * Revise the JVM runtime.
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Currently blocked by #101, #98, #95, #104
floatanddoubleas threshold types (XGBoost usesfloat; LightGBM usesdouble).Goal: end of this month
cc @mpuccio @jbagaipo @Yang-HangWA
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