ROperator_EyeLike.hxx

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#ifndef TMVA_SOFIE_ROPERATOR_EyeLike
#define TMVA_SOFIE_ROPERATOR_EyeLike
 
#include "TMVA/SOFIE_common.hxx"
#include "TMVA/ROperator.hxx"
#include "TMVA/RModel.hxx"
 
#include <sstream>
 
namespace TMVA{
namespace Experimental{
namespace SOFIE{
 
class ROperator_EyeLike final : public ROperator
{
 
private:
 
   int fdtype = static_cast<int>(ETensorType::FLOAT); //Default value
   int fk = 0;
   std::string fNX;
   std::string fNY;
   std::vector<size_t> fShape;
 
public:
   ROperator_EyeLike(){}
   ROperator_EyeLike(int dtype, int k, std::string nameX, std::string nameY):
      fdtype(dtype), fk(k), fNX(UTILITY::Clean_name(nameX)), fNY(UTILITY::Clean_name(nameY)){
         fInputTensorNames = { fNX };
         fOutputTensorNames = { fNY };
      }
 
   std::vector<ETensorType> TypeInference(std::vector<ETensorType> input){
      return input;
   }
 
   std::vector<std::vector<size_t>> ShapeInference(std::vector<std::vector<size_t>> input){
      auto ret = input; //suggest copy to compiler
      return ret;
   }
 
   void Initialize(RModel& model) override {
      if (model.CheckIfTensorAlreadyExist(fNX) == false){   //input must be a graph input, or already initialized intermediate tensor
         throw std::runtime_error("TMVA SOFIE EyeLike Op Input Tensor is not found in model");
      }
      fShape = model.GetTensorShape(fNX);
      if (fShape.size() != 2)
         throw std::runtime_error("TMVA SOFIE EyeLike Op Input Tensor is not of rank 2");
 
      if(fdtype){
        ETensorType extractedType = static_cast<ETensorType>(fdtype);
        model.AddIntermediateTensor(fNY, extractedType, fShape);
      }
      else{
        model.AddIntermediateTensor(fNY, model.GetTensorType(fNX), fShape);
      }
   }
 
 
   std::string Generate(std::string OpName){
      OpName = "op_" + OpName;
      if (fShape.empty()){
         throw std::runtime_error("TMVA SOFIE Operator EyeLike called to Generate without being initialized first");
      }
      auto length = ConvertShapeToLength(fShape);
      auto stride = TMVA::Experimental::SOFIE::UTILITY::ComputeStrideFromShape(fShape);
      std::stringstream out;
      out << SP << "///--------EyeLike operator\n" << std::endl;
      // add a dummy statement to avoid warning for unused input
      out << SP << "(void) tensor_" << fNX << ";\n";
 
      out << SP << "std::fill(tensor_" << fNY << ", tensor_" << fNY << " + " << length << ","
          << 0 << ");\n";
      out << SP << "for (int i = 0; i < " << fShape[0] << "; i++) {\n";
      out << SP << SP << "int j = i +" << fk << ";\n";
      out << SP << SP << "if (j >= 0 && j < " << fShape[1] << ")\n";
      out << SP << SP << SP << "tensor_" << fNY << "[i * " << fShape[1] << "+ j] = 1;\n";
      out << SP << "}\n";
      return out.str();
   }
 
};
 
}//SOFIE
}//Experimental
}//TMVA
 
 
#endif //TMVA_SOFIE_ROPERATOR_EyeLike