#include <ONNXWrapper.h>

Collaboration diagram for ONNXWrapper:

Public Member Functions
	ONNXWrapper (const std::string model_path)

std::map< std::string, std::vector< float > >	Run (std::map< std::string, std::vector< float >> inputs, int n_batches=1)

const std::map< std::string, std::vector< int64_t > >	GetModelInputs ()

const std::map< std::string, std::vector< int64_t > >	GetModelOutputs ()

const std::map< std::string, std::string >	GetMETAData ()

std::string	GetMETADataByKey (const char *key)

const std::vector< int64_t > &	getInputShape (int input_nr)

const std::vector< int64_t > &	getOutputShape (int output_nr)

const std::vector< const char * > &	getInputNames ()

const std::vector< const char * > &	getOutputNames ()

int	getNumInputs () const

int	getNumOutputs () const

Private Member Functions
const std::vector< int64_t >	getShape (Ort::TypeInfo model_info)

Private Attributes
std::string	m_modelName

std::string	m_modelPath

size_t	m_nr_inputs

size_t	m_nr_output

std::map< std::string, std::vector< int64_t > >	m_input_dims

std::map< std::string, std::vector< int64_t > >	m_output_dims

std::unique_ptr< Ort::Session >	m_onnxSession

std::unique_ptr< Ort::Env >	m_onnxEnv

Ort::SessionOptions	m_session_options

Ort::AllocatorWithDefaultOptions	m_allocator

std::vector< const char * >	m_output_names

std::vector< const char * >	m_input_names

Detailed Description

Definition at line 16 of file ONNXWrapper.h.

Constructor & Destructor Documentation

◆ ONNXWrapper()

ONNXWrapper::ONNXWrapper ( const std::string model_path )

Definition at line 3 of file ONNXWrapper.cxx.

                                                    {
     
     // Use the path resolver to find the location of the network .onnx file
     m_modelPath = PathResolverFindCalibFile(model_path);
  
     //  init onnx envi
     m_onnxEnv = std::make_unique< Ort::Env >(ORT_LOGGING_LEVEL_WARNING, "");
  
     // initialize session options if needed
     m_session_options.SetIntraOpNumThreads(1);
     m_session_options.SetGraphOptimizationLevel(
       GraphOptimizationLevel::ORT_ENABLE_EXTENDED);
  
  
     // Initialise the ONNX environment and session using the above options and the model name
     m_onnxSession = std::make_unique<Ort::Session>(*m_onnxEnv,
                                                    m_modelPath.c_str(),
                                                    m_session_options);
  
     // get the input nodes
     m_nr_inputs = m_onnxSession->GetInputCount();
  
     // get the output nodes
     m_nr_output = m_onnxSession->GetOutputCount();
      
  
     // iterate over all input nodes
     for (std::size_t i = 0; i < m_nr_inputs; i++) {
       const char* input_name = m_onnxSession->GetInputNameAllocated(i, m_allocator).release();
  
       m_input_names.push_back(input_name);
  
       m_input_dims[input_name] = getShape(m_onnxSession->GetInputTypeInfo(i));
     }
  
     // iterate over all output nodes
     for(std::size_t i = 0; i < m_nr_output; i++ ) {
       const char* output_name = m_onnxSession->GetOutputNameAllocated(i, m_allocator).release();
  
       m_output_names.push_back(output_name);
  
       m_output_dims[output_name] = getShape(m_onnxSession->GetOutputTypeInfo(i));
  
     }
 }

Member Function Documentation

◆ getInputNames()

const std::vector< const char * > & ONNXWrapper::getInputNames ( )

Definition at line 154 of file ONNXWrapper.cxx.

                                                         {
   //put the model access for input here
   return m_input_names;
 }

◆ getInputShape()

const std::vector< int64_t > & ONNXWrapper::getInputShape ( int input_nr = 0 )

Definition at line 164 of file ONNXWrapper.cxx.

                                                                   {
   //put the model access for input here
   std::vector<const char*> names = getInputNames();
   return m_input_dims[names.at(input_nr)];
 }

◆ GetMETAData()

const std::map< std::string, std::string > ONNXWrapper::GetMETAData ( )

Definition at line 136 of file ONNXWrapper.cxx.

                                                             {
   std::map<std::string, std::string> METAData_map;
   auto metadata = m_onnxSession->GetModelMetadata();
  
   auto keys = metadata.GetCustomMetadataMapKeysAllocated(m_allocator);
   // auto status = OrtApi::ModelMetadataGetCustomMetadataMapKeys(metadata, m_allocator, keys, nkeys)
   for (size_t i = 0; i < keys.size(); i++) {
     METAData_map[keys[i].get()]=this->GetMETADataByKey(keys[i].get());
   }
  
   return METAData_map;
 }

◆ GetMETADataByKey()

std::string ONNXWrapper::GetMETADataByKey ( const char * key )

Definition at line 149 of file ONNXWrapper.cxx.

                                                        {
   auto metadata = m_onnxSession->GetModelMetadata();
   return metadata.LookupCustomMetadataMapAllocated(key, m_allocator).get();
 }

◆ GetModelInputs()

const std::map< std::string, std::vector< int64_t > > ONNXWrapper::GetModelInputs ( )

Definition at line 118 of file ONNXWrapper.cxx.

                                                                         {
   std::map<std::string, std::vector<int64_t>> ModelInputINFO_map;
  
   for(std::size_t i = 0; i < m_nr_inputs; i++ ) {
     ModelInputINFO_map[m_input_names.at(i)] = m_input_dims[m_input_names.at(i)];
   }
   return ModelInputINFO_map;
 }

◆ GetModelOutputs()

const std::map< std::string, std::vector< int64_t > > ONNXWrapper::GetModelOutputs ( )

Definition at line 127 of file ONNXWrapper.cxx.

                                                                          {
   std::map<std::string, std::vector<int64_t>> ModelOutputINFO_map;
  
   for(std::size_t i = 0; i < m_nr_output; i++ ) {
     ModelOutputINFO_map[m_output_names.at(i)] = m_output_dims[m_output_names.at(i)];
   }
   return ModelOutputINFO_map;
 }

◆ getNumInputs()

int ONNXWrapper::getNumInputs ( ) const

Definition at line 176 of file ONNXWrapper.cxx.

176 { return m_input_names.size(); }

◆ getNumOutputs()

int ONNXWrapper::getNumOutputs ( ) const

Definition at line 177 of file ONNXWrapper.cxx.

177 { return m_output_names.size(); }

◆ getOutputNames()

const std::vector< const char * > & ONNXWrapper::getOutputNames ( )

Definition at line 159 of file ONNXWrapper.cxx.

                                                          {
   //put the model access for outputs here
   return m_output_names;
 }

◆ getOutputShape()

const std::vector< int64_t > & ONNXWrapper::getOutputShape ( int output_nr = 0 )

Definition at line 170 of file ONNXWrapper.cxx.

                                                                     {
   //put the model access for outputs here
   std::vector<const char*> names = getOutputNames();
   return m_output_dims[names.at(output_nr)];
 }

◆ getShape()

const std::vector< int64_t > ONNXWrapper::getShape ( Ort::TypeInfo model_info )

private

Definition at line 179 of file ONNXWrapper.cxx.

                                                                      {
       auto tensor_info = model_info.GetTensorTypeAndShapeInfo();
       std::vector<int64_t> dims = tensor_info.GetShape();
       dims[0]=1;
       return dims;
     }

◆ Run()

std::map< std::string, std::vector< float > > ONNXWrapper::Run	(	std::map< std::string, std::vector< float >>	inputs,
		int	n_batches = `1`
	)

Definition at line 49 of file ONNXWrapper.cxx.

                                                              {
     for ( const auto &p : inputs ) // check for valid dimensions between batches and inputs
     {
       uint64_t n=1;
       for (uint64_t i:m_input_dims[p.first])
         {
           n*=i;
         }
     if ( (p.second.size() % n) != 0){
       
       throw std::invalid_argument("For input '"+p.first+"' length not compatible with model. Expect a multiple of "+std::to_string(n)+", got "+std::to_string(p.second.size()));
     }
     if (  p.second.size()!=(n_batches*n)){
       throw std::invalid_argument("Number of batches not compatible with length of vector");
     }
     }
     // Create a CPU tensor to be used as input
     Ort::MemoryInfo memory_info("Cpu", OrtDeviceAllocator, 0, OrtMemTypeDefault);
  
     // define input tensor
     std::vector<Ort::Value> output_tensor;
     std::vector<Ort::Value> input_tensor;
  
     // add the inputs to vector
     for ( const auto &p : m_input_dims )   
     {        
       std::vector<int64_t> in_dims = p.second;
       in_dims.at(0) = n_batches;
       input_tensor.push_back(Ort::Value::CreateTensor<float>(memory_info,
                                                             inputs[p.first].data(),
                                                             inputs[p.first].size(),
                                                             in_dims.data(),
                                                             in_dims.size()));
     }
  
     // init output tensor and fill with zeros
     std::map<std::string, std::vector<float>> outputs;
     for ( const auto &p : m_output_dims ) {
       std::vector<int64_t> out_dims = p.second;
       out_dims.at(0) = n_batches;
       // init output
       int length = 1;
       for(auto i : out_dims){ length*=i; }
       std::vector<float> output(length,0);
       // std::vector<float> output(m_output_dims[i][1], 0.0);
       outputs[p.first] = output;
       output_tensor.push_back(Ort::Value::CreateTensor<float>(memory_info,
                                                             outputs[p.first].data(),
                                                             outputs[p.first].size(),
                                                             out_dims.data(),
                                                             out_dims.size()));
     }
  
     Ort::Session& session = *m_onnxSession;
  
     // run the model
     session.Run(Ort::RunOptions{nullptr},
                 m_input_names.data(),
                 input_tensor.data(),
                 2,
                 m_output_names.data(),
                 output_tensor.data(),
                 2); 
  
     return outputs;
     }

Member Data Documentation

◆ m_allocator

Ort::AllocatorWithDefaultOptions ONNXWrapper::m_allocator

private

Definition at line 41 of file ONNXWrapper.h.

◆ m_input_dims

std::map<std::string, std::vector<int64_t> > ONNXWrapper::m_input_dims

private

Definition at line 31 of file ONNXWrapper.h.

◆ m_input_names

std::vector<const char*> ONNXWrapper::m_input_names

private

Definition at line 47 of file ONNXWrapper.h.

◆ m_modelName

std::string ONNXWrapper::m_modelName

private

Definition at line 21 of file ONNXWrapper.h.

◆ m_modelPath

std::string ONNXWrapper::m_modelPath

private

Definition at line 22 of file ONNXWrapper.h.

◆ m_nr_inputs

size_t ONNXWrapper::m_nr_inputs

private

Definition at line 27 of file ONNXWrapper.h.

◆ m_nr_output

size_t ONNXWrapper::m_nr_output

private

Definition at line 28 of file ONNXWrapper.h.

◆ m_onnxEnv

std::unique_ptr< Ort::Env > ONNXWrapper::m_onnxEnv

private

Definition at line 37 of file ONNXWrapper.h.

◆ m_onnxSession

std::unique_ptr<Ort::Session> ONNXWrapper::m_onnxSession

private

Definition at line 36 of file ONNXWrapper.h.

◆ m_output_dims

std::map<std::string, std::vector<int64_t> > ONNXWrapper::m_output_dims

private

Definition at line 32 of file ONNXWrapper.h.

◆ m_output_names

std::vector<const char*> ONNXWrapper::m_output_names

private

Definition at line 46 of file ONNXWrapper.h.

◆ m_session_options

Ort::SessionOptions ONNXWrapper::m_session_options

private

Definition at line 40 of file ONNXWrapper.h.

The documentation for this class was generated from the following files:

Public Member Functions

Private Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ ONNXWrapper()

Member Function Documentation

◆ getInputNames()

◆ getInputShape()

◆ GetMETAData()

◆ GetMETADataByKey()

◆ GetModelInputs()

◆ GetModelOutputs()

◆ getNumInputs()

◆ getNumOutputs()

◆ getOutputNames()

◆ getOutputShape()

◆ getShape()

◆ Run()

Member Data Documentation

◆ m_allocator

◆ m_input_dims

◆ m_input_names

◆ m_modelName

◆ m_modelPath

◆ m_nr_inputs

◆ m_nr_output

◆ m_onnxEnv

◆ m_onnxSession

◆ m_output_dims

◆ m_output_names

◆ m_session_options