ROperator_Tanh.hxx

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#ifndef TMVA_SOFIE_ROPERATOR_Tanh
#define TMVA_SOFIE_ROPERATOR_Tanh
 
#include "TMVA/SOFIE_common.hxx"
#include "TMVA/ROperator.hxx"
#include "TMVA/RModel.hxx"
 
#include <sstream>
 
namespace TMVA{
namespace Experimental{
namespace SOFIE{
 
template <typename T>
class ROperator_Tanh final : public ROperator
{
 
private:
 
   std::string fNX;
   std::string fNY;
   std::vector<Dim> fShape;
 
public:
   ROperator_Tanh(){}
   ROperator_Tanh(std::string nameX, std::string nameY):
      fNX(UTILITY::Clean_name(nameX)), fNY(UTILITY::Clean_name(nameY)){
         fInputTensorNames = { fNX };
         fOutputTensorNames = { fNY };
      }
 
   void Initialize(RModel& model) override {
       //input must be a graph input, or already initialized intermediate tensor
      if (model.CheckIfTensorAlreadyExist(fNX) == false){
        throw std::runtime_error("TMVA SOFIE Tanh Op Input Tensor is not found in model");
      }
      fShape = model.GetDimTensorShape(fNX);
      model.AddIntermediateTensor(fNY, model.GetTensorType(fNX), fShape);
 
   }
 
 
   std::string Generate(std::string OpName) override {
      OpName = "op_" + OpName;
      if (fShape.empty()) {
         throw std::runtime_error("TMVA SOFIE Tanh operator called to Generate without being initialized first");
      }
      std::stringstream out;
      auto length = ConvertDimShapeToLength(fShape);
      out << "\n//------ TANH\n";
      // Deliberately std::tanh: rewriting this as (e^{2x}-1)/(e^{2x}+1) (or
      // similar exp-based formulas) returns NaN for x > ~44 in single
      // precision (exp overflows to inf, giving inf/inf) and loses all
      // relative accuracy near x = 0 through cancellation. The measured
      // speedup was only ~20-25%; the real performance lever is compiling
      // the generated code so the loop vectorizes (e.g. -ffast-math with
      // glibc uses the SIMD tanhf from libmvec, ~4x faster).
      out << SP << "for (size_t id = 0; id < " << length << " ; id++){\n";
      out << SP << SP << "tensor_" << fNY << "[id] = std::tanh(tensor_" << fNX << "[id]);\n";
      out << SP << "}\n";
      return out.str();
   }
 
   std::vector<std::string> GetStdLibs() override { return { std::string("cmath") };}
};
 
}//SOFIE
}//Experimental
}//TMVA
 
 
#endif //TMVA_SOFIE_ROPERATOR_Tanh