3#include "onnx_proto3.pb.h"
6namespace Experimental {
11 std::vector<std::string> inputs;
12 size_t size = nodeproto.input_size();
14 for (
int i = 0; i < nodeproto.input_size(); ++i) {
15 auto input_name = nodeproto.input(i);
22 throw std::runtime_error(
"TMVA::SOFIE ONNX Parser Concat op has input tensor" + input_name +
23 " but its type is not yet registered");
25 inputs.emplace_back(input_name);
28 std::unique_ptr<ROperator> op;
29 std::string output_name = nodeproto.output(0);
32 int attr_new_axis = 0;
33 for (
int_t i = 0; i < nodeproto.attribute_size(); i++) {
34 std::string attribute_name = nodeproto.attribute(i).name();
35 if (attribute_name ==
"axis")
36 attr_axis = nodeproto.attribute(i).i();
37 else if (attribute_name ==
"new_axis")
38 attr_new_axis = nodeproto.attribute(i).i();
42 op.reset(
new ROperator_Concat(inputs, attr_axis, attr_new_axis, output_name));
size_t size(const MatrixT &matrix)
retrieve the size of a square matrix
bool IsRegisteredTensorType(const std::string &)
void RegisterTensorType(const std::string &, ETensorType)
ETensorType GetTensorType(const std::string &name)
ParserFuncSignature ParseConcat
std::function< std::unique_ptr< ROperator >(RModelParser_ONNX &, const onnx::NodeProto &)> ParserFuncSignature
create variable transformations