164 const int batchSize = inputTensorValues.rows();
170 if (inputNodeDims[0] == -1)
172 inputNodeDims[0] = batchSize;
174 if (outputNodeDims[0] == -1)
176 outputNodeDims[0] = batchSize;
179 if(inputNodeDims[1] != inputTensorValues.cols())
181 throw std::runtime_error(
"runONNXInference: feature size doesn't match the input size: inputSize required: " +
std::to_string(inputNodeDims[1]) +
" inputSize provided: " +
std::to_string(inputTensorValues.cols()));
184 if (batchSize != 1 &&(inputNodeDims[0] != batchSize || outputNodeDims[0] != batchSize))
186 throw std::runtime_error(
"runONNXInference: batch size doesn't match the input or output node size");
190 Ort::MemoryInfo memoryInfo = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault);
191 Ort::Value inputTensor = Ort::Value::CreateTensor<float>(memoryInfo, inputTensorValues.data(), inputTensorValues.size(), inputNodeDims.data(), inputNodeDims.size());
193 if (!inputTensor.IsTensor())
195 throw std::runtime_error(
"runONNXInference: conversion of input to Tensor failed. ");
198 Ort::RunOptions run_options;
199 std::vector<Ort::Value> outputTensors =
205 if (!outputTensors[0].IsTensor() || (outputTensors.size() !=
m_outputNodeNames.size())) {
206 throw std::runtime_error(
"runONNXInference: calculation of output failed. ");
210 std::map<int, Eigen::MatrixXf> outputTensorMap;
211 size_t numOutputNodes =
m_session->GetOutputCount();
212 for (
size_t i=0;
i<numOutputNodes;
i++){
215 float*
output = outputTensors.at(
i).GetTensorMutableData<
float>();
216 Ort::TypeInfo outputTypeInfo =
m_session->GetOutputTypeInfo(
i);
217 auto outputTensorInfo = outputTypeInfo.GetTensorTypeAndShapeInfo();
220 outputNodeDims = outputTensorInfo.GetShape();
222 int nNodes = outputNodeDims.size() > 1 ? outputNodeDims[1] : 1;
223 Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic> batchMatrix(batchSize, nNodes);
224 for (
int j = 0; j < batchSize; j++)
226 Eigen::VectorXf
vec(nNodes);
227 for (
int k = 0;
k<nNodes;
k++)
229 float val =
output[j * outputNodeDims[1] +
k];
232 batchMatrix.row(j) =
vec;
234 outputTensorMap[
i] = std::move(batchMatrix);
236 return outputTensorMap;