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ROperator_LeakyRelu.hxx
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1#ifndef TMVA_SOFIE_ROPERATOR_LeakyRelu
2#define TMVA_SOFIE_ROPERATOR_LeakyRelu
3
5#include "TMVA/ROperator.hxx"
6#include "TMVA/RModel.hxx"
7
8#include <sstream>
9
10namespace TMVA{
11namespace Experimental{
12namespace SOFIE{
13
14template <typename T>
15class ROperator_LeakyRelu final : public ROperator
16{
17
18private:
19
20 /* Attributes*/
21 float falpha=0.01; //default value
22 std::string fNX;
23 std::string fNY;
24 std::vector<size_t> fShape;
25 std::string fType;
26
27public:
29 ROperator_LeakyRelu(float alpha,std::string nameX, std::string nameY):
30 falpha(alpha),fNX(UTILITY::Clean_name(nameX)), fNY(UTILITY::Clean_name(nameY))
31 {
32 if(std::is_same<T, float>::value){
33 fType = "float";
34 }
35 else{
36 throw
37 std::runtime_error("TMVA SOFIE Encountered unsupported type parsing a Leaky Relu operator");
38 }
39 }
40
41 std::vector<ETensorType> TypeInference(std::vector<ETensorType> input){
42 return input;
43 }
44
45 std::vector<std::vector<size_t>> ShapeInference(std::vector<std::vector<size_t>> input){
46 auto ret = input; //suggest copy to compiler
47 return ret;
48 }
49
50 void Initialize(RModel& model){
51 if (model.CheckIfTensorAlreadyExist(fNX) == false){ //input must be a graph input, or already initialized intermediate tensor
52 throw std::runtime_error("TMVA SOFIE Leaky Relu Op Input Tensor is not found in model");
53 }
54 fShape = model.GetTensorShape(fNX);
56 }
57
58
59 std::string Generate(std::string OpName){
60 OpName = "op_" + OpName;
61 if (fShape.empty()) {
62 throw std::runtime_error("TMVA SOFIE Operator Leaky Relu called to Generate without being initialized first");
63 }
64 std::stringstream out;
66
67 out << SP << "float " << OpName << "_alpha = " << std::setprecision(std::numeric_limits<float>::max_digits10) << falpha << ";\n";
68
69 out << "\n//------ LEAKY RELU\n";
70 out << SP << "for (int id = 0; id < " << length << " ; id++){\n";
71 out << SP << SP << "tensor_" << fNY << "[id] = ((tensor_" << fNX << "[id] >= 0 )? tensor_" << fNX << "[id] : "<< OpName << "_alpha * tensor_"<< fNX<<"[id]);\n";
72 out << SP << "}\n";
73 return out.str();
74 }
75
76};
77
78}//SOFIE
79}//Experimental
80}//TMVA
81
82
83#endif //TMVA_SOFIE_ROPERATOR_LeakyRelu
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void input
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t GCValues_t GetPrimarySelectionOwner GetDisplay GetScreen GetColormap GetNativeEvent const char const char dpyName wid window const char font_name cursor keysym reg const char only_if_exist regb h Point_t winding char text const char depth char const char Int_t count const char ColorStruct_t color const char Pixmap_t Pixmap_t PictureAttributes_t attr const char char ret_data h unsigned char height h length
const ETensorType & GetTensorType(std::string name)
Definition RModel.cxx:94
void AddIntermediateTensor(std::string tensor_name, ETensorType type, std::vector< Dim > dim_shape)
Definition RModel.cxx:203
bool CheckIfTensorAlreadyExist(std::string tensor_name)
Definition RModel.cxx:122
const std::vector< size_t > & GetTensorShape(std::string name)
Definition RModel.cxx:56
std::vector< std::vector< size_t > > ShapeInference(std::vector< std::vector< size_t > > input)
std::vector< ETensorType > TypeInference(std::vector< ETensorType > input)
ROperator_LeakyRelu(float alpha, std::string nameX, std::string nameY)
const std::string SP
space used to correctly indent the generated C++ code
Definition ROperator.hxx:41
std::size_t ConvertShapeToLength(std::vector< size_t > shape)
create variable transformations