TMVA::Experimental Namespace Reference

Namespaces
namespace	Internal
namespace	SOFIE

Classes
class	RBDT
class	RReader
	A replacement for the TMVA::Reader legacy interface. More...
class	RSofieReader
	TMVA::RSofieReader class for reading external Machine Learning models in ONNX files and performing the inference using SOFIE. More...
class	SofieFunctorHelper
	Helper class used by SOFIEFunctor to wrap the infer signature interface to RDataFrame. More...
class	SofieFunctorHelper< std::index_sequence< N... >, Session_t, T >

Functions
template<std::size_t N, typename T , typename F >
auto	Compute (F &&f) -> Internal::ComputeHelper< std::make_index_sequence< N >, T, F >
	Helper to pass TMVA model to RDataFrame.Define nodes.
template<std::size_t N, typename Session_t >
auto	SofieFunctor (unsigned int nslots=0, const std::string &weightsFile="") -> SofieFunctorHelper< std::make_index_sequence< N >, Session_t, float >
	SofieFunctor : used to wrap the infer function of the generated model by SOFIE in a RDF compatible signature.

Function Documentation

Compute()

template<std::size_t N, typename T , typename F >

auto TMVA::Experimental::Compute

(

F &&

f

)

-> Internal::ComputeHelper<std::make_index_sequence<N>, T, F>

Helper to pass TMVA model to RDataFrame.Define nodes.

Definition at line 37 of file RInferenceUtils.hxx.

SofieFunctor()

template<std::size_t N, typename Session_t >

auto TMVA::Experimental::SofieFunctor	(	unsigned int	nslots = 0,
		const std::string &	weightsFile = "" ) -> SofieFunctorHelper<std::make_index_sequence<N>, Session_t, float>

SofieFunctor : used to wrap the infer function of the generated model by SOFIE in a RDF compatible signature.

The number of slots is an optional parameter used to create multiple SOFIE Sessions, which can be run in a parallel model evaluation. One should use as number of slots the number of slots used by RDataFrame. By default, in case of nslots=0, only a single Session will be created and the Functor cannot be run in parallel. Examples of using the SofieFunctor are the C++ tutorial TMVA_SOFIE_RDataFrame.C and the Python tutorial TMVA_SOFIE_RDataFrame.py which makes use of the ROOT JIT to compile on the fly the generated SOFIE model.

Definition at line 64 of file SOFIEHelpers.hxx.