1#ifndef TMVA_SOFIE_ROPERATOR_TRANSPOSE
2#define TMVA_SOFIE_ROPERATOR_TRANSPOSE
12namespace Experimental{
38 fNData(UTILITY::Clean_name(nameData)),
fNOutput(UTILITY::Clean_name(nameOutput)) {
46 if (
input.size() > 1)
throw std::runtime_error(
"TMVA SOFIE Tranpose Op Shape Inference only need 1 input tensor");
49 throw std::runtime_error(
"TMVA SOFIE Tranpose Op - Invalid axes attributes");
51 std::vector<size_t> output_shape(
fAttrPerm.size());
52 for (
size_t i = 0; i <
fAttrPerm.size(); i++){
55 std::vector<std::vector<size_t>> ret;
56 ret.push_back(output_shape);
63 throw std::runtime_error(
"TMVA SOFIE Tranpose Op Input Tensor is not found in model");
68 for (
int i =
fShapeData.size() - 1; i >= 0; i--){
72 std::vector<std::vector<size_t>> inputs = {
fShapeData };
78 OpName =
"op_" + OpName;
80 throw std::runtime_error(
"TMVA SOFIE Transpose Op called to Generate without being initialized first");
88 std::stringstream out;
99 out <<
SP <<
"///------- Transpose operator\n" << std::endl;
100 out <<
SP <<
"for (size_t id = 0; id < " <<
length <<
" ; id++){\n";
103 std::vector<std::string> i_out(dim);
104 for (
int k =0; k < dim; k++){
108 i_out[k] =
"(id % " + std::to_string(outStrides[k-1]) +
")";
110 i_out[k] +=
" / " + std::to_string(outStrides[k]);
114 for (
int k =0; k < dim; k++){
117 assert(
l >= 0 &&
l < dim);
118 out <<
"( " << i_out[
l] <<
" )";
120 out <<
" * " << inStrides[k];
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void data
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)
void AddIntermediateTensor(std::string tensor_name, ETensorType type, std::vector< std::size_t > shape)
bool CheckIfTensorAlreadyExist(std::string tensor_name)
const std::vector< size_t > & GetTensorShape(std::string name)
ROperator_Transpose(std::string nameData, std::string nameOutput)
std::string Generate(std::string OpName)
std::vector< size_t > fShapeData
void Initialize(RModel &model)
std::vector< size_t > fShapeOutput
std::vector< std::vector< size_t > > ShapeInference(std::vector< std::vector< size_t > > input)
std::vector< ETensorType > TypeInference(std::vector< ETensorType > input)
ROperator_Transpose(std::vector< int_t > attr_perm, std::string nameData, std::string nameOutput)
std::vector< int_t > fAttrPerm
const std::string SP
space used to correctly indent the generated C++ code
std::vector< size_t > ComputeStrideFromShape(const std::vector< size_t > &shape)
compute stride of a tensor given its shape (assume layout is row-major)
create variable transformations