1#ifndef TMVA_SOFIE_ROPERATOR_TOPK
2#define TMVA_SOFIE_ROPERATOR_TOPK
11namespace Experimental {
51 if (
input.size() != 2) {
52 throw std::runtime_error(
"TMVA SOFIE TopK Op Shape Inference needs exactly 2 input tensors");
55 auto shape =
input[0];
59 return {shape, shape};
66 throw std::runtime_error(
"TMVA SOFIE TopK Op Input Tensor is not found in model");
70 throw std::runtime_error(
"TMVA SOFIE TopK Op Input Tensor i.e. K is not found in model");
81 std::runtime_error(
"TMVA::SOFIE ONNX TopK op axis = "+ std::to_string(
fAttrAxis) +
" value exeeds size of tensor " +
fNX+
" of size "+
fShapeX.size()+
" .");
115 throw std::runtime_error(
"TMVA SOFIE Operator TopK called to Generate without being initialized first");
117 std::stringstream out;
120 out <<
"\n" <<
SP <<
"//------ TopK\n";
132 out <<
SP <<
"std::vector<std::pair<float,int64_t>> elements(" <<
n_elements <<
");\n";
135 out <<
SP <<
"for (size_t i = 0; i < " <<
n_before <<
"; i++) {\n";
136 out <<
SP <<
SP <<
"size_t xoffset = i*" <<
strideX[axis-1] <<
";\n";
137 out <<
SP <<
SP <<
"size_t yoffset = i*" <<
strideY[axis-1] <<
";\n";
140 out <<
SP <<
"size_t xoffset = 0;\n";
141 out <<
SP <<
"size_t yoffset = 0;\n";
144 out <<
SP <<
"for (size_t j = 0; j < " <<
n_after <<
"; j++) {\n";
146 out <<
SP <<
"const size_t j = 0;\n";
149 out <<
SP <<
SP <<
"for (size_t l = 0; l < " <<
n_elements <<
"; l++) {\n";
150 out <<
SP <<
SP <<
SP <<
"elements[l] = std::make_pair(tensor_" <<
fNX <<
"[xoffset + " <<
strideX[axis] <<
"*l + j], l);\n";
151 out <<
SP <<
SP <<
"}\n";
155 out<<
SP<<
SP <<
"std::partial_sort(elements.begin(),elements.begin()+" <<
fK <<
",elements.end()," <<
156 "[](std::pair<float,int64_t>a,std::pair<float,int64_t>b){return (a.first!=b.first) ? (a.first>b.first) : a.second < b.second;});\n";
159 out<<
SP<<
SP <<
"std::partial_sort(elements.begin(),elements.begin()+" <<
fK <<
",elements.end()," <<
160 "[](std::pair<float,int64_t>a,std::pair<float,int64_t>b){return (a.first!=b.first) ? (a.first<b.first) : a.second < b.second;});\n";
163 out<<
SP<<
SP <<
"std::partial_sort(elements.begin(),elements.begin()+" <<
fK <<
",elements.end());\n";
166 out <<
SP <<
SP <<
"for (size_t l = 0; l < " <<
fK <<
"; l++) {\n";
167 out <<
SP <<
SP <<
SP <<
"tensor_" <<
fNVal <<
"[yoffset + " <<
strideY[axis] <<
"*l + j] = elements[l].first;\n";
168 out <<
SP <<
SP <<
SP <<
"tensor_" <<
fNInd <<
"[yoffset + " <<
strideY[axis] <<
"*l + j] = elements[l].second;\n";
169 out <<
SP <<
SP <<
"}\n";
size_t size(const MatrixT &matrix)
retrieve the size of a square matrix
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
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
void AddIntermediateTensor(std::string tensor_name, ETensorType type, std::vector< Dim > dim_shape)
bool CheckIfTensorAlreadyExist(std::string tensor_name)
const ETensorType & GetTensorType(std::string name) const
const std::vector< size_t > & GetTensorShape(std::string name) const
std::shared_ptr< void > GetInitializedTensorData(std::string tensor_name)
void SetNotWritableInitializedTensor(const std::string &tensor_name)
std::string Generate(std::string OpName) override
std::vector< std::vector< size_t > > ShapeInference(std::vector< std::vector< size_t > > input) override
std::vector< size_t > fShapeX
std::vector< size_t > fShapeY
std::vector< ETensorType > TypeInference(std::vector< ETensorType > input) override
ROperator_TopK(int attr_axis, int attr_largest, int attr_sorted, std::string nameK, std::string nameX, std::string nameVal, std::string nameInd)
void Initialize(RModel &model) override
std::vector< std::string_view > fInputTensorNames
const std::string SP
space used to correctly indent the generated C++ code
std::vector< std::string_view > fOutputTensorNames
std::vector< size_t > ComputeStrideFromShape(const std::vector< size_t > &shape)
compute stride of a tensor given its shape (assume layout is row-major)
std::string ConvertTypeToString(ETensorType type)
std::size_t ConvertShapeToLength(std::vector< size_t > shape)
create variable transformations