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C++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVA
We report the latest development in ROOT/TMVA, a new system that takes trained ONNX deep learning models and emits C++ code that can be easily included and invoked for fast inference of the model, with minimal dependency. We present an overview of the current solutions for conducting inference in C+...
| Autores principales: | , |
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| Lenguaje: | eng |
| Publicado: |
2021
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| Acceso en línea: | https://dx.doi.org/10.1051/epjconf/202125103040 http://cds.cern.ch/record/2780369 |