Tool using the ONNX Runtime C++ API to retrieve constituents based model for boson jet tagging. More...

#include <JSSMLTool.h>

Inheritance diagram for AthONNX::JSSMLTool:

Collaboration diagram for AthONNX::JSSMLTool:

Public Member Functions
	JSSMLTool (const std::string &name)
virtual StatusCode	initialize () override
	Function initialising the tool.
virtual double	retrieveConstituentsScore (std::vector< TH2D > Images) const override
	Function executing the tool for a single event.
virtual double	retrieveConstituentsScore (std::vector< std::vector< float > > constituents) const override
virtual double	retrieveConstituentsScore (std::vector< std::vector< float > > constituents, std::vector< std::vector< std::vector< float > > > interactions) const override
virtual double	retrieveConstituentsScore (std::vector< std::vector< float > > constituents, std::vector< std::vector< std::vector< float > > > interactions, std::vector< std::vector< float > > mask) const override
virtual double	retrieveHighLevelScore (std::map< std::string, double > JSSVars) const override
virtual std::vector< float >	retrieveConstituentsScoreMultiClass (const std::vector< std::vector< float > > &constituents, const std::vector< std::vector< std::vector< float > > > &interactions, const std::vector< std::vector< float > > &mask) const override
std::vector< float >	ReadJetImagePixels (std::vector< TH2D > Images) const
std::vector< float >	ReadJSSInputs (std::map< std::string, double > JSSVars) const
std::vector< int >	ReadOutputLabels () const
StatusCode	SetScaler (const std::map< std::string, std::vector< double > > &scaler) override
virtual void	print () const
	Print the state of the tool.
ServiceHandle< StoreGateSvc > &	evtStore ()
	The standard `StoreGateSvc` (event store) Returns (kind of) a pointer to the `StoreGateSvc`.
const ServiceHandle< StoreGateSvc > &	detStore () const
	The standard `StoreGateSvc/DetectorStore` Returns (kind of) a pointer to the `StoreGateSvc`.
virtual StatusCode	sysInitialize () override
	Perform system initialization for an algorithm.
virtual StatusCode	sysStart () override
	Handle START transition.
virtual std::vector< Gaudi::DataHandle * >	inputHandles () const override
	Return this algorithm's input handles.
virtual std::vector< Gaudi::DataHandle * >	outputHandles () const override
	Return this algorithm's output handles.
Gaudi::Details::PropertyBase &	declareProperty (Gaudi::Property< T, V, H > &t)
void	updateVHKA (Gaudi::Details::PropertyBase &)
MsgStream &	msg () const
bool	msgLvl (const MSG::Level lvl) const
Additional helper functions, not directly mimicking Athena
template<class T>
const T *	getProperty (const std::string &name) const
	Get one of the tool's properties.
const std::string &	msg_level_name () const __attribute__((deprecated))
	A deprecated function for getting the message level's name.
const std::string &	getName (const void *ptr) const
	Get the name of an object that is / should be in the event store.
SG::sgkey_t	getKey (const void *ptr) const
	Get the (hashed) key of an object that is in the event store.

Public Attributes
std::unique_ptr< Ort::Session >	m_session
std::unique_ptr< Ort::Env >	m_env
std::map< std::string, std::vector< double > >	m_scaler
std::map< int, std::string >	m_JSSInputMap

Protected Member Functions
void	renounceArray (SG::VarHandleKeyArray &handlesArray)
	remove all handles from I/O resolution
std::enable_if_t< std::is_void_v< std::result_of_t< decltype(&T::renounce)(T)> > &&!std::is_base_of_v< SG::VarHandleKeyArray, T > &&std::is_base_of_v< Gaudi::DataHandle, T >, void >	renounce (T &h)
void	extraDeps_update_handler (Gaudi::Details::PropertyBase &ExtraDeps)
	Add StoreName to extra input/output deps as needed.

Private Types
typedef ServiceHandle< StoreGateSvc >	StoreGateSvc_t

Private Member Functions
Gaudi::Details::PropertyBase &	declareGaudiProperty (Gaudi::Property< T, V, H > &hndl, const SG::VarHandleKeyType &)
	specialization for handling Gaudi::Property<SG::VarHandleKey>

Private Attributes
std::string	m_modelFileName
	Name of the model file to load.
std::string	m_pixelFileName
std::string	m_labelFileName
std::vector< int64_t >	m_input_node_dims
size_t	m_num_input_nodes {}
std::vector< const char * >	m_input_node_names
std::vector< int64_t >	m_output_node_dims
size_t	m_num_output_nodes {}
std::vector< const char * >	m_output_node_names
int	m_nPixelsX {}
int	m_nPixelsY {}
int	m_nPixelsZ {}
int	m_nvars {}
StoreGateSvc_t	m_evtStore
	Pointer to StoreGate (event store by default).
StoreGateSvc_t	m_detStore
	Pointer to StoreGate (detector store by default).
std::vector< SG::VarHandleKeyArray * >	m_vhka
bool	m_varHandleArraysDeclared

Detailed Description

Tool using the ONNX Runtime C++ API to retrieve constituents based model for boson jet tagging.

this is inspired from the general athena example here: https://gitlab.cern.ch/atlas/athena/-/blob/21.2/Control/AthenaExamples/AthExOnnxRuntime/AthExOnnxRuntime/CxxApiAlgorithm.h

this is implementation is an extension from the one done in rel.21 https://gitlab.cern.ch/atlas/athena/-/tree/21.2/Reconstruction/Jet/AthOnnxRuntimeBJT as the plan is to move to use the central ONNX interface the tool has been merged with the BJT

monitoring jira ticket: https://its.cern.ch/jira/browse/ATLJETMET-1893

Author: Antonio Giannini anton.nosp@m.io.g.nosp@m.ianni.nosp@m.ni@c.nosp@m.ern.c.nosp@m.h

Definition at line 46 of file JSSMLTool.h.

Member Typedef Documentation

◆ StoreGateSvc_t

typedef ServiceHandle<StoreGateSvc> AthCommonDataStore< AthCommonMsg< AlgTool > >::StoreGateSvc_t

privateinherited

Definition at line 388 of file AthCommonDataStore.h.

Constructor & Destructor Documentation

◆ JSSMLTool()

AthONNX::JSSMLTool::JSSMLTool ( const std::string & name )

Definition at line 76 of file JSSMLTool.cxx.

                                           :
    AsgTool(name)
  {
    declareProperty("ModelPath", m_modelFileName);
    declareProperty("nPixelsX", m_nPixelsX);
    declareProperty("nPixelsY", m_nPixelsY);
    declareProperty("nPixelsZ", m_nPixelsZ);
  }

Member Function Documentation

◆ declareGaudiProperty()

Gaudi::Details::PropertyBase & AthCommonDataStore< AthCommonMsg< AlgTool > >::declareGaudiProperty	(	Gaudi::Property< T, V, H > &	hndl,
		const SG::VarHandleKeyType &	)

inlineprivateinherited

specialization for handling Gaudi::Property<SG::VarHandleKey>

Definition at line 156 of file AthCommonDataStore.h.

  {
    return *AthCommonDataStore<PBASE>::declareProperty(hndl.name(),
                                                       hndl.value(), 
                                                       hndl.documentation());
 
  }

◆ declareProperty()

Gaudi::Details::PropertyBase & AthCommonDataStore< AthCommonMsg< AlgTool > >::declareProperty ( Gaudi::Property< T, V, H > & t )

inlineinherited

Definition at line 145 of file AthCommonDataStore.h.

                                                                     {
    typedef typename SG::HandleClassifier<T>::type htype;
    return AthCommonDataStore<PBASE>::declareGaudiProperty(t, htype());
  }

◆ detStore()

const ServiceHandle< StoreGateSvc > & AthCommonDataStore< AthCommonMsg< AlgTool > >::detStore ( ) const

inlineinherited

The standard StoreGateSvc/DetectorStore Returns (kind of) a pointer to the StoreGateSvc.

Definition at line 95 of file AthCommonDataStore.h.

95{ return m_detStore; }

AthCommonDataStore< AthCommonMsg< AlgTool > >::m_detStore

StoreGateSvc_t m_detStore

Definition AthCommonDataStore.h:393

◆ evtStore()

ServiceHandle< StoreGateSvc > & AthCommonDataStore< AthCommonMsg< AlgTool > >::evtStore ( )

inlineinherited

The standard StoreGateSvc (event store) Returns (kind of) a pointer to the StoreGateSvc.

Definition at line 85 of file AthCommonDataStore.h.

85{ return m_evtStore; }

AthCommonDataStore< AthCommonMsg< AlgTool > >::m_evtStore

StoreGateSvc_t m_evtStore

Definition AthCommonDataStore.h:390

◆ extraDeps_update_handler()

void AthCommonDataStore< AthCommonMsg< AlgTool > >::extraDeps_update_handler ( Gaudi::Details::PropertyBase & ExtraDeps )

protectedinherited

Add StoreName to extra input/output deps as needed.

use the logic of the VarHandleKey to parse the DataObjID keys supplied via the ExtraInputs and ExtraOuputs Properties to add the StoreName if it's not explicitly given

◆ getKey()

SG::sgkey_t asg::AsgTool::getKey ( const void * ptr ) const

inherited

Get the (hashed) key of an object that is in the event store.

This is a bit of a special one. StoreGateSvc and xAOD::Event both provide ways for getting the SG::sgkey_t key for an object that is in the store, based on a bare pointer. But they provide different interfaces for doing so.

In order to allow tools to efficiently perform this operation, they can use this helper function.

See also: asg::AsgTool::getName

Parameters

ptr	The bare pointer to the object that the event store should know about

Returns: The hashed key of the object in the store. If not found, an invalid (zero) key.

Definition at line 119 of file AsgTool.cxx.

                                                    {
 
#ifdef XAOD_STANDALONE
      // In case we use @c xAOD::Event, we have a direct function call
      // for this.
      return evtStore()->event()->getKey( ptr );
#else
      const SG::DataProxy* proxy = evtStore()->proxy( ptr );
      return ( proxy == nullptr ? 0 : proxy->sgkey() );
#endif // XAOD_STANDALONE
   }

◆ getName()

const std::string & asg::AsgTool::getName ( const void * ptr ) const

inherited

Get the name of an object that is / should be in the event store.

This is a bit of a special one. StoreGateSvc and xAOD::Event both provide ways for getting the std::string name for an object that is in the store, based on a bare pointer. But they provide different interfaces for doing so.

In order to allow tools to efficiently perform this operation, they can use this helper function.

See also: asg::AsgTool::getKey

Parameters

ptr	The bare pointer to the object that the event store should know about

Returns: The string name of the object in the store. If not found, an empty string.

Definition at line 106 of file AsgTool.cxx.

                                                            {
 
#ifdef XAOD_STANDALONE
      // In case we use @c xAOD::Event, we have a direct function call
      // for this.
      return evtStore()->event()->getName( ptr );
#else
      const SG::DataProxy* proxy = evtStore()->proxy( ptr );
      static const std::string dummy = "";
      return ( proxy == nullptr ? dummy : proxy->name() );
#endif // XAOD_STANDALONE
   }

◆ getProperty()

template<class T>

const T * asg::AsgTool::getProperty ( const std::string & name ) const

inherited

Get one of the tool's properties.

◆ initialize()

StatusCode AthONNX::JSSMLTool::initialize ( void )

overridevirtual

Function initialising the tool.

Reimplemented from asg::AsgTool.

Definition at line 86 of file JSSMLTool.cxx.

                                    {
 
    // Access the service.    
    // Find the model file.    
    ATH_MSG_INFO( "Using model file: " << m_modelFileName );
    
    // Set up the ONNX Runtime session.
    Ort::SessionOptions sessionOptions;
    sessionOptions.SetIntraOpNumThreads( 1 );
    sessionOptions.SetGraphOptimizationLevel( ORT_ENABLE_BASIC );
 
    // according to the discussion here https://its.cern.ch/jira/browse/ATLASG-2866
    // this should reduce memory use while slowing things down slightly
    sessionOptions.DisableCpuMemArena();
 
    // declare an allocator
    Ort::AllocatorWithDefaultOptions allocator;
 
    // create session and load model into memory
    m_env = std::make_unique< Ort::Env >(ORT_LOGGING_LEVEL_WARNING, "");
    m_session = std::make_unique< Ort::Session >( *m_env,
                          m_modelFileName.c_str(),
                          sessionOptions );
    
    ATH_MSG_INFO( "Created the ONNX Runtime session" );
    
    m_num_input_nodes = m_session->GetInputCount();
    m_input_node_names.resize(m_num_input_nodes);
    
    for( std::size_t i = 0; i < m_num_input_nodes; i++ ) {
      // print input node names
      char* input_name = m_session->GetInputNameAllocated(i, allocator).release();
      ATH_MSG_DEBUG("Input "<<i<<" : "<<" name = "<<input_name);
      m_input_node_names[i] = input_name;
      // print input node types
      Ort::TypeInfo type_info = m_session->GetInputTypeInfo(i);
      auto tensor_info = type_info.GetTensorTypeAndShapeInfo();
      ONNXTensorElementDataType type = tensor_info.GetElementType();
      ATH_MSG_DEBUG("Input "<<i<<" : "<<" type = "<<type);
      
      // print input shapes/dims
      m_input_node_dims = tensor_info.GetShape();
      ATH_MSG_DEBUG("Input "<<i<<" : num_dims = "<<m_input_node_dims.size());
      for (std::size_t j = 0; j < m_input_node_dims.size(); j++){
        if(m_input_node_dims[j]<0)
          m_input_node_dims[j] =1;
        ATH_MSG_DEBUG("Input"<<i<<" : dim "<<j<<" = "<<m_input_node_dims[j]);
      }  
    }
    
    m_num_output_nodes = m_session->GetOutputCount();
    m_output_node_names.resize(m_num_output_nodes);
    
    for( std::size_t i = 0; i < m_num_output_nodes; i++ ) {
      // print output node names
      char* output_name = m_session->GetOutputNameAllocated(i, allocator).release();
      ATH_MSG_DEBUG("Output "<<i<<" : "<<" name = "<<output_name);
      m_output_node_names[i] = output_name;
      
      Ort::TypeInfo type_info = m_session->GetOutputTypeInfo(i);
      auto tensor_info = type_info.GetTensorTypeAndShapeInfo();
      ONNXTensorElementDataType type = tensor_info.GetElementType();
      ATH_MSG_DEBUG("Output "<<i<<" : "<<" type = "<<type);
      
      // print output shapes/dims
      m_output_node_dims = tensor_info.GetShape();
      ATH_MSG_INFO("Output "<<i<<" : num_dims = "<<m_output_node_dims.size());
      for (std::size_t j = 0; j < m_output_node_dims.size(); j++){
        if(m_output_node_dims[j]<0)
          m_output_node_dims[j] =1;
        ATH_MSG_INFO("Output"<<i<<" : dim "<<j<<" = "<<m_output_node_dims[j]);
      }  
    }
 
    // Return gracefully.
    return StatusCode::SUCCESS;
  } // end initialize ---

◆ inputHandles()

virtual std::vector< Gaudi::DataHandle * > AthCommonDataStore< AthCommonMsg< AlgTool > >::inputHandles ( ) const

overridevirtualinherited

Return this algorithm's input handles.

We override this to include handle instances from key arrays if they have not yet been declared. See comments on updateVHKA.

◆ msg()

MsgStream & AthCommonMsg< AlgTool >::msg ( ) const

inlineinherited

Definition at line 24 of file AthCommonMsg.h.

                                {
    return this->msgStream();
  }

◆ msg_level_name()

const std::string & asg::AsgTool::msg_level_name ( ) const

inherited

A deprecated function for getting the message level's name.

Instead of using this, weirdly named function, user code should get the string name of the current minimum message level (in case they really need it...), with:

MSG::name( msg().level() )

This function's name doesn't follow the ATLAS coding rules, and as such will be removed in the not too distant future.

Returns: The string name of the current minimum message level that's printed

Definition at line 101 of file AsgTool.cxx.

                                                  {
 
      return MSG::name( msg().level() );
   }

◆ msgLvl()

bool AthCommonMsg< AlgTool >::msgLvl ( const MSG::Level lvl ) const

inlineinherited

Definition at line 30 of file AthCommonMsg.h.

                                               {
    return this->msgLevel(lvl);
  }

◆ outputHandles()

virtual std::vector< Gaudi::DataHandle * > AthCommonDataStore< AthCommonMsg< AlgTool > >::outputHandles ( ) const

overridevirtualinherited

Return this algorithm's output handles.

We override this to include handle instances from key arrays if they have not yet been declared. See comments on updateVHKA.

◆ print()

void asg::AsgTool::print ( ) const

virtualinherited

Print the state of the tool.

Implements asg::IAsgTool.

Reimplemented in AsgHelloTool, HI::HIPileupTool, JetBottomUpSoftDrop, JetConstituentsRetriever, JetDumper, JetFinder, JetFromPseudojet, JetModifiedMassDrop, JetPileupLabelingTool, JetPruner, JetPseudojetRetriever, JetReclusterer, JetReclusteringTool, JetRecTool, JetRecursiveSoftDrop, JetSoftDrop, JetSplitter, JetSubStructureMomentToolsBase, JetToolRunner, JetTrimmer, JetTruthLabelingTool, and KtDeltaRTool.

Definition at line 131 of file AsgTool.cxx.

                             {
 
      ATH_MSG_INFO( "AsgTool " << name() << " @ " << this );
      return;
   }

◆ ReadJetImagePixels()

std::vector< float > AthONNX::JSSMLTool::ReadJetImagePixels ( std::vector< TH2D > Images ) const

Definition at line 17 of file JSSMLTool.cxx.

  {
 
    int n_rows = m_nPixelsX;
    int n_cols = m_nPixelsY;
    int n_colors = m_nPixelsZ;
 
    std::vector<float> input_tensor_values(n_rows*n_cols*n_colors);
 
    for(int iRow=0; iRow<n_rows; ++iRow){
      for(int iColumn=0; iColumn<n_cols; ++iColumn){
        for(int iColor=0; iColor<n_colors; ++iColor){
          input_tensor_values[ (n_colors*n_cols*iRow) + iColumn*n_colors + iColor] = Images[iColor].GetBinContent(iRow+1, iColumn+1);
        }
      }
    }
 
    return input_tensor_values;
  }

◆ ReadJSSInputs()

std::vector< float > AthONNX::JSSMLTool::ReadJSSInputs ( std::map< std::string, double > JSSVars ) const

Definition at line 39 of file JSSMLTool.cxx.

  {
 
    std::vector<float> input_tensor_values(m_nvars);
 
    // apply features scaling
    for(const auto & var : JSSVars){
      auto p = m_scaler.find(var.first);
      if (p == m_scaler.end()) continue;
      double mean = p->second[0];
      double std  = p->second[1];
      JSSVars[var.first] = (var.second - mean) / std;
    }
 
    // then dump it to a vector
    for(int v=0; v<m_nvars; ++v){
      if (auto found = m_JSSInputMap.find(v);found != m_JSSInputMap.end())[[likely]]{
        input_tensor_values[v] = JSSVars[found->second];
      }
    }
 
    return input_tensor_values;
  }

◆ ReadOutputLabels()

std::vector< int > AthONNX::JSSMLTool::ReadOutputLabels ( ) const

Definition at line 66 of file JSSMLTool.cxx.

  {
    std::vector<int> output_tensor_values(1);
 
    output_tensor_values[0] = 1;
 
    return output_tensor_values;
  }

◆ renounce()

std::enable_if_t< std::is_void_v< std::result_of_t< decltype(&T::renounce)(T)> > &&!std::is_base_of_v< SG::VarHandleKeyArray, T > &&std::is_base_of_v< Gaudi::DataHandle, T >, void > AthCommonDataStore< AthCommonMsg< AlgTool > >::renounce ( T & h )

inlineprotectedinherited

Definition at line 380 of file AthCommonDataStore.h.

  {
    h.renounce();
    PBASE::renounce (h);
  }

◆ renounceArray()

void AthCommonDataStore< AthCommonMsg< AlgTool > >::renounceArray ( SG::VarHandleKeyArray & handlesArray )

inlineprotectedinherited

remove all handles from I/O resolution

Definition at line 364 of file AthCommonDataStore.h.

                                                          {
    handlesArray.renounce();
  }

◆ retrieveConstituentsScore() [1/4]

double AthONNX::JSSMLTool::retrieveConstituentsScore ( std::vector< std::vector< float > > constituents ) const

overridevirtual

Implements AthONNX::IJSSMLTool.

Definition at line 212 of file JSSMLTool.cxx.

                                                                                            {
        
    // the format of the packed constituents is:
    // constituents.size() ---> 4, for example, (m pT, eta, phi)
    // constituents.at(0) ---> number of constituents
    // the packing can be done for any kind of low level inputs
    // i.e. PFO/UFO constituents, topo-towers, tracks, etc
    // they can be concatened one after the other in case of multiple inputs
 
    //*************************************************************************
    // Score the model using sample data, and inspect values
    // loading input data
 
    std::vector<int> output_tensor_values_ = ReadOutputLabels();
    
    int testSample = 0;    
    
    //preparing container to hold output data
    int output_tensor_values = output_tensor_values_[testSample]; 
 
    // prepare the inputs
    auto memory_info = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault);
    std::vector<Ort::Value> input_tensors;
    for (long unsigned int i=0; i<constituents.size(); i++) {
 
      // test
      std::vector<int64_t> const_dim = {1, static_cast<int64_t>(constituents.at(i).size())};
 
      input_tensors.push_back(Ort::Value::CreateTensor<float>(
        memory_info, 
        constituents.at(i).data(), constituents.at(i).size(), const_dim.data(), const_dim.size()
        )
      );
    }
 
    auto output_tensors = m_session->Run(Ort::RunOptions{nullptr}, m_input_node_names.data(), input_tensors.data(), m_input_node_names.size(), m_output_node_names.data(), m_output_node_names.size());
    assert(output_tensors.size() == 1 && output_tensors.front().IsTensor());
    
    // Get pointer to output tensor float values
    float* floatarr = output_tensors.front().GetTensorMutableData<float>();
    int arrSize = sizeof(*floatarr)/sizeof(floatarr[0]);
 
    // show  true label for the test input
    ATH_MSG_DEBUG("Label for the input test data  = "<<output_tensor_values);
    float ConstScore = -999;
    int max_index = 0;
    for (int i = 0; i < arrSize; i++){
      ATH_MSG_VERBOSE("Score for class "<<i<<" = "<<floatarr[i]<<std::endl);
      ATH_MSG_VERBOSE(" +++ Score for class "<<i<<" = "<<floatarr[i]<<std::endl);
      if (ConstScore<floatarr[i]){
        ConstScore = floatarr[i];
        max_index = i;
      }
    }
    ATH_MSG_DEBUG("Class: "<<max_index<<" has the highest score: "<<floatarr[max_index]);
    
    return ConstScore;
 
  } // end retrieve constituents score ----

◆ retrieveConstituentsScore() [2/4]

double AthONNX::JSSMLTool::retrieveConstituentsScore	(	std::vector< std::vector< float > >	constituents,
		std::vector< std::vector< std::vector< float > > >	interactions ) const

overridevirtual

Implements AthONNX::IJSSMLTool.

Definition at line 273 of file JSSMLTool.cxx.

                                                                                                                                                 {
        
    // the format of the constituents/interaction variables is:
    // constituents       ---> (nConstituents + nTowers, 7)
    // interactions       ---> (i, j, 4), with i, j in {nConstituents + nTowers}
    // the packing can be done for any kind of low level inputs
    // i.e. PFO/UFO constituents, topo-towers, tracks, etc
    // they can be concatened one after the other in case of multiple inputs
 
    //*************************************************************************
    // Score the model using sample data, and inspect values
    // loading input data
 
    std::vector<int> output_tensor_values_ = ReadOutputLabels();
    
    int testSample = 0;    
    
    //preparing container to hold output data
    int output_tensor_values = output_tensor_values_[testSample]; 
 
    // prepare the inputs
    auto memory_info = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault);
    std::vector<Ort::Value> input_tensors;
 
    // unroll the inputs
    std::vector<float> constituents_values; //(constituents.size()*7);
    for (long unsigned int i=0; i<constituents.size(); i++) {
      for (long unsigned int j=0; j<7; j++) {
        constituents_values.push_back(constituents.at(i).at(j));
      }
    }
 
    std::vector<float> interactions_values; //(interactions.size()*interactions.size()*4);
    for (long unsigned int i=0; i<interactions.size(); i++) {
      for (long unsigned int k=0; k<interactions.size(); k++) {
        for (long unsigned int j=0; j<4; j++) {
          interactions_values.push_back(interactions.at(i).at(k).at(j));
        }
      }
    }
 
    std::vector<int64_t> const_dim = {1, static_cast<int64_t>(constituents.size()), 7};
    input_tensors.push_back(Ort::Value::CreateTensor<float>(
      memory_info, 
      constituents_values.data(), constituents_values.size(), const_dim.data(), const_dim.size()
      )
    );
 
    std::vector<int64_t> inter_dim = {1, static_cast<int64_t>(constituents.size()), static_cast<int64_t>(constituents.size()), 4};
    input_tensors.push_back(Ort::Value::CreateTensor<float>(
      memory_info, 
      interactions_values.data(), interactions_values.size(), inter_dim.data(), inter_dim.size()
      )
    );
 
    auto output_tensors = m_session->Run(Ort::RunOptions{nullptr}, m_input_node_names.data(), input_tensors.data(), m_input_node_names.size(), m_output_node_names.data(), m_output_node_names.size());
    assert(output_tensors.size() == 1 && output_tensors.front().IsTensor());
    
    // Get pointer to output tensor float values
    float* floatarr = output_tensors.front().GetTensorMutableData<float>();
    int arrSize = sizeof(*floatarr)/sizeof(floatarr[0]);
 
    // show  true label for the test input
    ATH_MSG_DEBUG("Label for the input test data  = "<<output_tensor_values);
    float ConstScore = -999;
    int max_index = 0;
    for (int i = 0; i < arrSize; i++){
      ATH_MSG_VERBOSE("Score for class "<<i<<" = "<<floatarr[i]<<std::endl);
      ATH_MSG_VERBOSE(" +++ Score for class "<<i<<" = "<<floatarr[i]<<std::endl);
      if (ConstScore<floatarr[i]){
        ConstScore = floatarr[i];
        max_index = i;
      }
    }
    ATH_MSG_DEBUG("Class: "<<max_index<<" has the highest score: "<<floatarr[max_index]);
    
    return ConstScore;
 
  } // end retrieve constituents score ----

◆ retrieveConstituentsScore() [3/4]

double AthONNX::JSSMLTool::retrieveConstituentsScore	(	std::vector< std::vector< float > >	constituents,
		std::vector< std::vector< std::vector< float > > >	interactions,
		std::vector< std::vector< float > >	mask ) const

overridevirtual

Implements AthONNX::IJSSMLTool.

Definition at line 354 of file JSSMLTool.cxx.

                                                                                                                                                                                   {
      
    // the format of the constituents/interaction variables is:
    // constituents       ---> (nConstituents, 7)
    // interactions       ---> (i, j, 4), with i, j in {nConstituents}
    // masks              ---> (nConstituents, 1)
    // the packing can be done for any kind of low level inputs
    // i.e. PFO/UFO constituents, topo-towers, tracks, etc
    // they can be concatened one after the other in case of multiple inputs
 
    //*************************************************************************
    // Score the model using sample data, and inspect values
    // loading input data
 
    std::vector<int> output_tensor_values_ = ReadOutputLabels();
    
    int testSample = 0;    
    
    //preparing container to hold output data
    int output_tensor_values = output_tensor_values_[testSample]; 
 
    // prepare the inputs
    auto memory_info = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault);
    std::vector<Ort::Value> input_tensors;
 
    // unroll the inputs
    std::vector<float> constituents_values; 
    for (long unsigned int j=0; j<7; j++) {
      for (long unsigned int i=0; i<constituents.size(); i++) {
        constituents_values.push_back(constituents.at(i).at(j));
      }
    }
 
    std::vector<float> interactions_values; 
    for (long unsigned int k=0; k<4; k++) {
      for (long unsigned int i=0; i<interactions.size(); i++) {
        for (long unsigned int j=0; j<interactions.size(); j++) {
          interactions_values.push_back(interactions.at(i).at(j).at(k));
        }
      }
    }
 
    std::vector<float> mask_values; 
    for (long unsigned int j=0; j<1; j++) {
      for (long unsigned int i=0; i<mask.size(); i++) {
        mask_values.push_back(mask.at(i).at(j));
      }
    }
 
    std::vector<int64_t> const_dim = {1, 7, static_cast<int64_t>(constituents.size())};
    input_tensors.push_back(Ort::Value::CreateTensor<float>(
      memory_info, 
      constituents_values.data(), constituents_values.size(), const_dim.data(), const_dim.size()
      )
    );
 
    std::vector<int64_t> inter_dim = {1, 4, static_cast<int64_t>(interactions.size()), static_cast<int64_t>(interactions.size())};
    input_tensors.push_back(Ort::Value::CreateTensor<float>(
      memory_info, 
      interactions_values.data(), interactions_values.size(), inter_dim.data(), inter_dim.size()
      )
    );
 
    std::vector<int64_t> mask_dim = {1, 1, static_cast<int64_t>(mask.size())};
    input_tensors.push_back(Ort::Value::CreateTensor<float>(
      memory_info, 
      mask_values.data(), mask_values.size(), mask_dim.data(), mask_dim.size()
      )
    );
 
    auto output_tensors = m_session->Run(Ort::RunOptions{nullptr}, m_input_node_names.data(), input_tensors.data(), m_input_node_names.size(), m_output_node_names.data(), m_output_node_names.size());
    assert(output_tensors.size() == 1 && output_tensors.front().IsTensor());
    
    // Get pointer to output tensor float values
    float* floatarr = output_tensors.front().GetTensorMutableData<float>();
    int arrSize = sizeof(*floatarr)/sizeof(floatarr[0]);
 
    // show  true label for the test input
    ATH_MSG_DEBUG("Label for the input test data  = "<<output_tensor_values);
    float ConstScore = -999;
    int max_index = 0;
    for (int i = 0; i < arrSize; i++){
      ATH_MSG_VERBOSE("Score for class "<<i<<" = "<<floatarr[i]<<std::endl);
      ATH_MSG_VERBOSE(" +++ Score for class "<<i<<" = "<<floatarr[i]<<std::endl);
      if (ConstScore<floatarr[i]){
        ConstScore = floatarr[i];
        max_index = i;
      }
    }
    ATH_MSG_DEBUG("Class: "<<max_index<<" has the highest score: "<<floatarr[max_index]);
 
    return ConstScore;
 
  } // end retrieve constituents score ----  

◆ retrieveConstituentsScore() [4/4]

double AthONNX::JSSMLTool::retrieveConstituentsScore ( std::vector< TH2D > Images ) const

overridevirtual

Function executing the tool for a single event.

Implements AthONNX::IJSSMLTool.

Definition at line 165 of file JSSMLTool.cxx.

                                                                          {
        
    //*************************************************************************
    // Score the model using sample data, and inspect values
 
    // preparing container to hold input data
    size_t input_tensor_size = m_nPixelsX*m_nPixelsY*m_nPixelsZ;
    std::vector<float> input_tensor_values(input_tensor_size);
 
    // loading input data
    input_tensor_values = ReadJetImagePixels(std::move(Images));
    
    // preparing container to hold output data
    int testSample = 0;    
    std::vector<int> output_tensor_values_ = ReadOutputLabels();
    int output_tensor_values = output_tensor_values_[testSample]; 
 
    // create input tensor object from data values
    auto memory_info = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault);
    Ort::Value input_tensor = Ort::Value::CreateTensor<float>(memory_info, input_tensor_values.data(), input_tensor_size, m_input_node_dims.data(), m_input_node_dims.size());
    assert(input_tensor.IsTensor());
        
    auto output_tensors = m_session->Run(Ort::RunOptions{nullptr}, m_input_node_names.data(), &input_tensor, m_input_node_names.size(), m_output_node_names.data(), m_output_node_names.size());
    assert(output_tensors.size() == 1 && output_tensors.front().IsTensor());
    
    // Get pointer to output tensor float values
    float* floatarr = output_tensors.front().GetTensorMutableData<float>();
    int arrSize = sizeof(*floatarr)/sizeof(floatarr[0]);
 
    // show  true label for the test input
    ATH_MSG_DEBUG("Label for the input test data  = "<<output_tensor_values);
    float ConstScore = -999;
    int max_index = 0;
    for (int i = 0; i < arrSize; i++){
      ATH_MSG_VERBOSE("Score for class "<<i<<" = "<<floatarr[i]<<std::endl);
      if (ConstScore<floatarr[i]){
        ConstScore = floatarr[i];
        max_index = i;
      }
    }
    ATH_MSG_DEBUG("Class: "<<max_index<<" has the highest score: "<<floatarr[max_index]);
    
    return ConstScore;
 
  } // end retrieve CNN score ----

◆ retrieveConstituentsScoreMultiClass()

std::vector< float > AthONNX::JSSMLTool::retrieveConstituentsScoreMultiClass	(	const std::vector< std::vector< float > > &	constituents,
		const std::vector< std::vector< std::vector< float > > > &	interactions,
		const std::vector< std::vector< float > > &	mask ) const

overridevirtual

Implements AthONNX::IJSSMLTool.

Definition at line 450 of file JSSMLTool.cxx.

                                                                                                                                                                                                                            {
      
    // the format of the constituents/interaction variables is:
    // constituents       ---> (nConstituents, 9)
    // interactions       ---> (i, j, 4), with i, j in {nConstituents}
    // masks              ---> (nConstituents, 1)
    // the packing can be done for any kind of low level inputs
    // i.e. PFO/UFO constituents, topo-towers, tracks, etc
    // they can be concatened one after the other in case of multiple inputs
 
    //*************************************************************************
    // Score the model using sample data, and inspect values
    // loading input data
 
    // input info
    const int nParticleVariables = 9;
    const int nInteractionVariables = 4;
 
    std::vector<int> output_tensor_values_ = ReadOutputLabels();
    
    int testSample = 0;    
    
    //preparing container to hold output data
    int output_tensor_values = output_tensor_values_[testSample]; 
 
    // prepare the inputs
    auto memory_info = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault);
    std::vector<Ort::Value> input_tensors;
 
    // unroll the inputs
    std::vector<float> constituents_values; 
    for (const auto& c : constituents)
      constituents_values.insert(constituents_values.end(), c.begin(), c.end());
 
    std::vector<float> interactions_values; 
    for (const auto& inter_i : interactions) {
      for (const auto& inter_j : inter_i)
        interactions_values.insert(interactions_values.end(), inter_j.begin(), inter_j.end());
    }
 
    std::vector<uint8_t> mask_values; 
    for (const auto& m : mask)
       mask_values.push_back(m[0]);
 
    std::vector<int64_t> const_dim = {1, static_cast<int64_t>(constituents.size()), nParticleVariables};
    input_tensors.push_back(Ort::Value::CreateTensor<float>(
      memory_info, 
      constituents_values.data(), constituents_values.size(), const_dim.data(), const_dim.size()
      )
    );
 
    std::vector<int64_t> inter_dim = {1, static_cast<int64_t>(interactions.size()), static_cast<int64_t>(interactions.size()), nInteractionVariables};
    input_tensors.push_back(Ort::Value::CreateTensor<float>(
      memory_info, 
      interactions_values.data(), interactions_values.size(), inter_dim.data(), inter_dim.size()
      )
    );
 
    std::vector<int64_t> mask_dim = {1, static_cast<int64_t>(mask.size())};
    input_tensors.push_back(Ort::Value::CreateTensor<bool>(
      memory_info, 
      reinterpret_cast<bool*>(mask_values.data()),
      mask_values.size(), mask_dim.data(), mask_dim.size()
      )
    );
 
    std::vector<Ort::Value> output_tensors = m_session->Run(Ort::RunOptions{nullptr}, m_input_node_names.data(), input_tensors.data(), m_input_node_names.size(), m_output_node_names.data(), m_output_node_names.size());
    assert(output_tensors.front().IsTensor());
 
    // Get pointer to output tensor float values
    float* floatarr = output_tensors.front().GetTensorMutableData<float>();
    auto info = output_tensors.front().GetTensorTypeAndShapeInfo();
    size_t arrSize = info.GetElementCount();
 
    // show  true label for the test input
    ATH_MSG_DEBUG("Label for the input test data  = "<<output_tensor_values);
    std::vector<float> ConstScores;
    for (long unsigned int i = 0; i < arrSize; i++){
      ATH_MSG_VERBOSE(" +++ Score for class " << i << " = " << floatarr[i]);
      ConstScores.push_back(floatarr[i]);
    }
 
    return ConstScores;
 
  } // end retrieve constituents score ----  

◆ retrieveHighLevelScore()

double AthONNX::JSSMLTool::retrieveHighLevelScore ( std::map< std::string, double > JSSVars ) const

overridevirtual

Implements AthONNX::IJSSMLTool.

Definition at line 537 of file JSSMLTool.cxx.

                                                                                  {
        
    //*************************************************************************
    // Score the model using sample data, and inspect values
    
    //preparing container to hold input data
    size_t input_tensor_size = m_nvars;
    std::vector<float> input_tensor_values(m_nvars);
 
    // loading input data
    input_tensor_values = ReadJSSInputs(std::move(JSSVars));
    
    // preparing container to hold output data
    int testSample = 0; 
    std::vector<int> output_tensor_values_ = ReadOutputLabels();
    int output_tensor_values = output_tensor_values_[testSample]; 
    
    // create input tensor object from data values
    auto memory_info = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault);
    
    // we need a multiple tensor input structure for DisCo model
    Ort::Value input1 = Ort::Value::CreateTensor<float>(memory_info, const_cast<float*>(input_tensor_values.data()), input_tensor_size, m_input_node_dims.data(), m_input_node_dims.size());
    std::vector<float> empty = {1.};
    Ort::Value input2 = Ort::Value::CreateTensor<float>(memory_info, empty.data(), 1, m_input_node_dims.data(), m_input_node_dims.size());
    Ort::Value input3 = Ort::Value::CreateTensor<float>(memory_info, empty.data(), 1, m_input_node_dims.data(), m_input_node_dims.size());
    Ort::Value input4 = Ort::Value::CreateTensor<float>(memory_info, empty.data(), 1, m_input_node_dims.data(), m_input_node_dims.size());
    std::vector<Ort::Value> input_tensor;
    std::vector<int64_t> aaa = {1, m_nvars};
    input_tensor.emplace_back(
      Ort::Value::CreateTensor<float>(memory_info, input_tensor_values.data(), input_tensor_size, aaa.data(), aaa.size())
    );
    input_tensor.emplace_back(
      Ort::Value::CreateTensor<float>(memory_info, input_tensor_values.data(), input_tensor_size, m_input_node_dims.data(), m_input_node_dims.size())
    );
    input_tensor.emplace_back(
      Ort::Value::CreateTensor<float>(memory_info, input_tensor_values.data(), input_tensor_size, m_input_node_dims.data(), m_input_node_dims.size())
    );
    input_tensor.emplace_back(
      Ort::Value::CreateTensor<float>(memory_info, input_tensor_values.data(), input_tensor_size, m_input_node_dims.data(), m_input_node_dims.size())
    );
        
    auto output_tensors = m_session->Run(Ort::RunOptions{nullptr}, m_input_node_names.data(), input_tensor.data(), m_input_node_names.size(), m_output_node_names.data(), m_output_node_names.size());
    assert(output_tensors.size() == 1 && output_tensors.front().IsTensor());
    
    // Get pointer to output tensor float values
    float* floatarr = output_tensors.front().GetTensorMutableData<float>();
    int arrSize = sizeof(*floatarr)/sizeof(floatarr[0]);
 
    // show  true label for the test input
    ATH_MSG_DEBUG("Label for the input test data  = "<<output_tensor_values);
    float HLScore = -999;
    int max_index = 0;
    for (int i = 0; i < arrSize; i++){
      ATH_MSG_VERBOSE("Score for class "<<i<<" = "<<floatarr[i]<<std::endl);
      if (HLScore<floatarr[i]){
          HLScore = floatarr[i];
          max_index = i;
      }
    }
    ATH_MSG_DEBUG("Class: "<<max_index<<" has the highest score: "<<floatarr[max_index]);
    
    return HLScore;
 
  } // end retrieve HighLevel score ----

◆ SetScaler()

StatusCode AthONNX::JSSMLTool::SetScaler ( const std::map< std::string, std::vector< double > > & scaler )

overridevirtual

Implements AthONNX::IJSSMLTool.

Definition at line 603 of file JSSMLTool.cxx.

                                                                                    {
    m_scaler = scaler;
 
    // ToDo:
    // this will have an overriding config as property
    m_JSSInputMap = {
      {0,"pT"}, {1,"CNN"}, {2,"D2"}, {3,"nTracks"}, {4,"ZCut12"},
      {5,"Tau1_wta"}, {6,"Tau2_wta"}, {7,"Tau3_wta"},
      {8,"KtDR"}, {9,"Split12"}, {10,"Split23"},
      {11,"ECF1"}, {12,"ECF2"}, {13,"ECF3"},
      {14,"Angularity"}, {15,"FoxWolfram0"}, {16,"FoxWolfram2"},
      {17,"Aplanarity"}, {18,"PlanarFlow"}, {19,"Qw"},
    };
    m_nvars = m_JSSInputMap.size();
 
    return StatusCode::SUCCESS;
  }

◆ sysInitialize()

virtual StatusCode AthCommonDataStore< AthCommonMsg< AlgTool > >::sysInitialize ( )

overridevirtualinherited

Perform system initialization for an algorithm.

We override this to declare all the elements of handle key arrays at the end of initialization. See comments on updateVHKA.

Reimplemented in asg::AsgMetadataTool, AthCheckedComponent< AthAlgTool >, and AthCheckedComponent<::AthAlgTool >.

◆ sysStart()

virtual StatusCode AthCommonDataStore< AthCommonMsg< AlgTool > >::sysStart ( )

overridevirtualinherited

Handle START transition.

We override this in order to make sure that conditions handle keys can cache a pointer to the conditions container.

◆ updateVHKA()

void AthCommonDataStore< AthCommonMsg< AlgTool > >::updateVHKA ( Gaudi::Details::PropertyBase & )

inlineinherited

Definition at line 308 of file AthCommonDataStore.h.

                                               {
    // debug() << "updateVHKA for property " << p.name() << " " << p.toString() 
    //         << "  size: " << m_vhka.size() << endmsg;
    for (auto &a : m_vhka) {
      std::vector<SG::VarHandleKey*> keys = a->keys();
      for (auto k : keys) {
        k->setOwner(this);
      }
    }
  }

Member Data Documentation

◆ m_detStore

StoreGateSvc_t AthCommonDataStore< AthCommonMsg< AlgTool > >::m_detStore

privateinherited

Pointer to StoreGate (detector store by default).

Definition at line 393 of file AthCommonDataStore.h.

◆ m_env

std::unique_ptr< Ort::Env > AthONNX::JSSMLTool::m_env

Definition at line 75 of file JSSMLTool.h.

◆ m_evtStore

StoreGateSvc_t AthCommonDataStore< AthCommonMsg< AlgTool > >::m_evtStore

privateinherited

Pointer to StoreGate (event store by default).

Definition at line 390 of file AthCommonDataStore.h.

◆ m_input_node_dims

std::vector<int64_t> AthONNX::JSSMLTool::m_input_node_dims

private

Definition at line 88 of file JSSMLTool.h.

◆ m_input_node_names

std::vector<const char*> AthONNX::JSSMLTool::m_input_node_names

private

Definition at line 90 of file JSSMLTool.h.

◆ m_JSSInputMap

std::map<int, std::string> AthONNX::JSSMLTool::m_JSSInputMap

Definition at line 78 of file JSSMLTool.h.

◆ m_labelFileName

std::string AthONNX::JSSMLTool::m_labelFileName

private

Definition at line 85 of file JSSMLTool.h.

◆ m_modelFileName

std::string AthONNX::JSSMLTool::m_modelFileName

private

Name of the model file to load.

Definition at line 83 of file JSSMLTool.h.

◆ m_nPixelsX

int AthONNX::JSSMLTool::m_nPixelsX {}

private

Definition at line 98 of file JSSMLTool.h.

98{}, m_nPixelsY{}, m_nPixelsZ{};

◆ m_nPixelsY

int AthONNX::JSSMLTool::m_nPixelsY {}

private

Definition at line 98 of file JSSMLTool.h.

98{}, m_nPixelsY{}, m_nPixelsZ{};

◆ m_nPixelsZ

int AthONNX::JSSMLTool::m_nPixelsZ {}

private

Definition at line 98 of file JSSMLTool.h.

98{}, m_nPixelsY{}, m_nPixelsZ{};

◆ m_num_input_nodes

size_t AthONNX::JSSMLTool::m_num_input_nodes {}

private

Definition at line 89 of file JSSMLTool.h.

89{};

◆ m_num_output_nodes

size_t AthONNX::JSSMLTool::m_num_output_nodes {}

private

Definition at line 94 of file JSSMLTool.h.

94{};

◆ m_nvars

int AthONNX::JSSMLTool::m_nvars {}

private

Definition at line 100 of file JSSMLTool.h.

100{};

◆ m_output_node_dims

std::vector<int64_t> AthONNX::JSSMLTool::m_output_node_dims

private

Definition at line 93 of file JSSMLTool.h.

◆ m_output_node_names

std::vector<const char*> AthONNX::JSSMLTool::m_output_node_names

private

Definition at line 95 of file JSSMLTool.h.

◆ m_pixelFileName

std::string AthONNX::JSSMLTool::m_pixelFileName

private

Definition at line 84 of file JSSMLTool.h.

◆ m_scaler

std::map<std::string, std::vector<double> > AthONNX::JSSMLTool::m_scaler

Definition at line 77 of file JSSMLTool.h.

◆ m_session

std::unique_ptr< Ort::Session > AthONNX::JSSMLTool::m_session

Definition at line 74 of file JSSMLTool.h.

◆ m_varHandleArraysDeclared

bool AthCommonDataStore< AthCommonMsg< AlgTool > >::m_varHandleArraysDeclared

privateinherited

Definition at line 399 of file AthCommonDataStore.h.

◆ m_vhka

std::vector<SG::VarHandleKeyArray*> AthCommonDataStore< AthCommonMsg< AlgTool > >::m_vhka

privateinherited

Definition at line 398 of file AthCommonDataStore.h.

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

Public Member Functions

Public Attributes

Protected Member Functions

Private Types

Private Member Functions

Private Attributes

Detailed Description

Member Typedef Documentation

◆ StoreGateSvc_t

Constructor & Destructor Documentation

◆ JSSMLTool()

Member Function Documentation

◆ declareGaudiProperty()

◆ declareProperty()

◆ detStore()

◆ evtStore()

◆ extraDeps_update_handler()

◆ getKey()

◆ getName()

◆ getProperty()

◆ initialize()

◆ inputHandles()

◆ msg()

◆ msg_level_name()

◆ msgLvl()

◆ outputHandles()

◆ print()

◆ ReadJetImagePixels()

◆ ReadJSSInputs()

◆ ReadOutputLabels()

◆ renounce()

◆ renounceArray()

◆ retrieveConstituentsScore() [1/4]

◆ retrieveConstituentsScore() [2/4]

◆ retrieveConstituentsScore() [3/4]

◆ retrieveConstituentsScore() [4/4]

◆ retrieveConstituentsScoreMultiClass()

◆ retrieveHighLevelScore()

◆ SetScaler()

◆ sysInitialize()

◆ sysStart()

◆ updateVHKA()

Member Data Documentation

◆ m_detStore

◆ m_env

◆ m_evtStore

◆ m_input_node_dims

◆ m_input_node_names

◆ m_JSSInputMap

◆ m_labelFileName

◆ m_modelFileName

◆ m_nPixelsX

◆ m_nPixelsY

◆ m_nPixelsZ

◆ m_num_input_nodes

◆ m_num_output_nodes

◆ m_nvars

◆ m_output_node_dims

◆ m_output_node_names

◆ m_pixelFileName

◆ m_scaler

◆ m_session

◆ m_varHandleArraysDeclared

◆ m_vhka