Create L3MuonTrajectorySeeds from L2 Muons in an outside-in manner. More...

Inheritance diagram for TSGForOIDNN:

Classes
struct	StrategyParameters
	Container for DNN outupts. More...

Public Member Functions
void	beginJob () override

void	produce (edm::StreamID sid, edm::Event &iEvent, const edm::EventSetup &iSetup) const override

	TSGForOIDNN (const edm::ParameterSet &iConfig)

	~TSGForOIDNN () override

Public Member Functions inherited from edm::global::EDProducer<>
	EDProducer ()=default

	EDProducer (const EDProducer &)=delete

bool	hasAbilityToProduceInBeginLumis () const final

bool	hasAbilityToProduceInBeginProcessBlocks () const final

bool	hasAbilityToProduceInBeginRuns () const final

bool	hasAbilityToProduceInEndLumis () const final

bool	hasAbilityToProduceInEndProcessBlocks () const final

bool	hasAbilityToProduceInEndRuns () const final

EDProducer &	operator= (const EDProducer &)=delete

bool	wantsGlobalLuminosityBlocks () const final

bool	wantsGlobalRuns () const final

bool	wantsInputProcessBlocks () const final

bool	wantsProcessBlocks () const final

bool	wantsStreamLuminosityBlocks () const final

bool	wantsStreamRuns () const final

Public Member Functions inherited from edm::global::EDProducerBase
	EDProducerBase ()

ModuleDescription const &	moduleDescription () const

	~EDProducerBase () override

Public Member Functions inherited from edm::ProducerBase
void	callWhenNewProductsRegistered (std::function< void(BranchDescription const &)> const &func)

std::vector< edm::ProductResolverIndex > const &	indiciesForPutProducts (BranchType iBranchType) const

	ProducerBase ()

std::vector< edm::ProductResolverIndex > const &	putTokenIndexToProductResolverIndex () const

std::vector< bool > const &	recordProvenanceList () const

void	registerProducts (ProducerBase , ProductRegistry , ModuleDescription const &)

std::function< void(BranchDescription const &)>	registrationCallback () const
	used by the fwk to register list of products More...

void	resolvePutIndicies (BranchType iBranchType, ModuleToResolverIndicies const &iIndicies, std::string const &moduleLabel)

TypeLabelList const &	typeLabelList () const
	used by the fwk to register the list of products of this module More...

	~ProducerBase () noexcept(false) override

Public Member Functions inherited from edm::EDConsumerBase
std::vector< ConsumesInfo >	consumesInfo () const

void	convertCurrentProcessAlias (std::string const &processName)
	Convert "@currentProcess" in InputTag process names to the actual current process name. More...

	EDConsumerBase ()

	EDConsumerBase (EDConsumerBase const &)=delete

	EDConsumerBase (EDConsumerBase &&)=default

ESResolverIndex const *	esGetTokenIndices (edm::Transition iTrans) const

std::vector< ESResolverIndex > const &	esGetTokenIndicesVector (edm::Transition iTrans) const

std::vector< ESRecordIndex > const &	esGetTokenRecordIndicesVector (edm::Transition iTrans) const

ProductResolverIndexAndSkipBit	indexFrom (EDGetToken, BranchType, TypeID const &) const

void	itemsMayGet (BranchType, std::vector< ProductResolverIndexAndSkipBit > &) const

void	itemsToGet (BranchType, std::vector< ProductResolverIndexAndSkipBit > &) const

std::vector< ProductResolverIndexAndSkipBit > const &	itemsToGetFrom (BranchType iType) const

void	labelsForToken (EDGetToken iToken, Labels &oLabels) const

void	modulesWhoseProductsAreConsumed (std::array< std::vector< ModuleDescription const > , NumBranchTypes > &modulesAll, std::vector< ModuleProcessName > &modulesInPreviousProcesses, ProductRegistry const &preg, std::map< std::string, ModuleDescription const *> const &labelsToDesc, std::string const &processName) const

EDConsumerBase const &	operator= (EDConsumerBase const &)=delete

EDConsumerBase &	operator= (EDConsumerBase &&)=default

bool	registeredToConsume (ProductResolverIndex, bool, BranchType) const

void	selectInputProcessBlocks (ProductRegistry const &productRegistry, ProcessBlockHelperBase const &processBlockHelperBase)

ProductResolverIndexAndSkipBit	uncheckedIndexFrom (EDGetToken) const

void	updateLookup (BranchType iBranchType, ProductResolverIndexHelper const &, bool iPrefetchMayGet)

void	updateLookup (eventsetup::ESRecordsToProductResolverIndices const &)

virtual	~EDConsumerBase () noexcept(false)

Static Public Member Functions
static void	fillDescriptions (edm::ConfigurationDescriptions &descriptions)

Static Public Member Functions inherited from edm::global::EDProducerBase
static const std::string &	baseType ()

static void	fillDescriptions (ConfigurationDescriptions &descriptions)

static void	prevalidate (ConfigurationDescriptions &descriptions)

Private Member Functions
void	evaluateClassifier (const std::unordered_map< std::string, float > &feature_map, tensorflow::Session *session, const pt::ptree &metadata, StrategyParameters &out, bool &dnnSuccess) const
	Evaluate DNN classifier. More...

void	evaluateRegressor (const std::unordered_map< std::string, float > &feature_map, tensorflow::Session session_HB, const pt::ptree &metadata_HB, tensorflow::Session session_HLIP, const pt::ptree &metadata_HLIP, tensorflow::Session *session_HLMuS, const pt::ptree &metadata_HLMuS, StrategyParameters &out, bool &dnnSuccess) const
	Evaluate DNN regressor. More...

void	initializeTensorflow () const

void	makeSeedsFromHitDoublets (const GeometricSearchDet &layer, const TrajectoryStateOnSurface &tsos, const Propagator &propagatorAlong, const Chi2MeasurementEstimatorBase &estimator, const MeasurementTrackerEvent &measurementTracker, const NavigationSchool &navSchool, unsigned int &hitDoubletSeedsMade, unsigned int &numSeedsMade, const unsigned int &maxHitDoubletSeeds, unsigned int &layerCount, std::vector< TrajectorySeed > &out) const
	Similar to makeSeedsFromHits, but seed is created only if there are compatible hits on two adjacent layers. More...

void	makeSeedsFromHits (const GeometricSearchDet &layer, const TrajectoryStateOnSurface &tsos, const Propagator &propagatorAlong, const Chi2MeasurementEstimatorBase &estimator, const MeasurementTrackerEvent &measurementTracker, unsigned int &hitSeedsMade, unsigned int &numSeedsMade, const unsigned int &maxHitSeeds, unsigned int &layerCount, std::vector< TrajectorySeed > &out) const
	Find hits on a given layer (TOB or TEC) and create seeds from updated TSOS with hit. More...

void	makeSeedsWithoutHits (const GeometricSearchDet &layer, const TrajectoryStateOnSurface &tsos, const Propagator &propagatorAlong, const Chi2MeasurementEstimatorBase &estimator, double errorSF, unsigned int &hitlessSeedsMade, unsigned int &numSeedsMade, std::vector< TrajectorySeed > &out) const
	Create seeds without hits on a given layer (TOB or TEC) More...

void	updateFeatureMap (std::unordered_map< std::string, float > &the_map, const reco::Track &l2, const TrajectoryStateOnSurface &tsos_IP, const TrajectoryStateOnSurface &tsos_MuS) const
	Update dictionary of inputs for DNN. More...

Private Attributes
const std::string	dnnMetadataPath_
	DNN metadata. More...

std::string	dnnModelPath_
	Settings for classifier. More...

std::string	dnnModelPath_HB_
	Settings for regressor. More...

std::string	dnnModelPath_HLIP_

std::string	dnnModelPath_HLMuS_

const std::string	estimatorName_
	Estimator used to find dets and TrajectoryMeasurements. More...

const double	fixedErrorRescalingForHitless_
	Rescale L2 parameter uncertainties (fixed error vs pT, eta) More...

const bool	getStrategyFromDNN_
	Get number of seeds to use from DNN output instead of "max..Seeds" parameters. More...

std::unique_ptr< tensorflow::GraphDef >	graphDef_

std::unique_ptr< tensorflow::GraphDef >	graphDef_HB_

std::unique_ptr< tensorflow::GraphDef >	graphDef_HLIP_

std::unique_ptr< tensorflow::GraphDef >	graphDef_HLMuS_

const double	maxEtaForTOB_
	Maximum eta value to activate searching in the TOB. More...

const unsigned int	maxHitDoubletSeeds_

const unsigned int	maxHitlessSeeds_
	Maximum number of hitless seeds for each L2. More...

const unsigned int	maxHitlessSeedsIP_

const unsigned int	maxHitlessSeedsMuS_

const unsigned int	maxHitSeeds_
	Maximum number of hitbased seeds for each L2. More...

const unsigned int	maxSeeds_
	Maximum number of seeds for each L2. More...

const edm::EDGetTokenT< MeasurementTrackerEvent >	measurementTrackerTag_

pt::ptree	metadata_

const double	minEtaForTEC_
	Minimum eta value to activate searching in the TEC. More...

const unsigned int	numOfHitsToTry_
	How many hits to try per layer. More...

const unsigned int	numOfLayersToTry_
	How many layers to try. More...

const edm::EDGetTokenT< reco::TrackCollection >	src_
	Labels for input collections. More...

const edm::ESGetToken< Chi2MeasurementEstimatorBase, TrackingComponentsRecord >	t_estimatorH_
	Tokens for ESHandle. More...

const edm::ESGetToken< GlobalTrackingGeometry, GlobalTrackingGeometryRecord >	t_geometryH_

const edm::ESGetToken< MagneticField, IdealMagneticFieldRecord >	t_magfieldH_

const edm::ESGetToken< NavigationSchool, NavigationSchoolRecord >	t_navSchool_

const edm::ESGetToken< Propagator, TrackingComponentsRecord >	t_propagatorAlongH_

const edm::ESGetToken< Propagator, TrackingComponentsRecord >	t_propagatorOppositeH_

const edm::ESGetToken< Propagator, TrackingComponentsRecord >	t_SHPOpposite_

const edm::ESGetToken< TrackerGeometry, TrackerDigiGeometryRecord >	t_tmpTkGeometryH_

tensorflow::Session *	tf_session_

tensorflow::Session *	tf_session_HB_

tensorflow::Session *	tf_session_HLIP_

tensorflow::Session *	tf_session_HLMuS_

const std::string	theCategory_

const std::unique_ptr< TrajectoryStateUpdator >	updator_

const bool	useRegressor_
	Whether to use DNN regressor (if false, will use classifier) More...

Additional Inherited Members
Public Types inherited from edm::global::EDProducerBase
typedef EDProducerBase	ModuleType

Public Types inherited from edm::ProducerBase
template<typename T >
using	BranchAliasSetterT = ProductRegistryHelper::BranchAliasSetterT< T >

using	ModuleToResolverIndicies = std::unordered_multimap< std::string, std::tuple< edm::TypeID const , const char , edm::ProductResolverIndex > >

typedef ProductRegistryHelper::TypeLabelList	TypeLabelList

Public Types inherited from edm::EDConsumerBase
typedef ProductLabels	Labels

Protected Member Functions inherited from edm::ProducerBase
template<Transition Tr = Transition::Event>
auto	produces (std::string instanceName) noexcept
	declare what type of product will make and with which optional label More...

template<Transition B>
BranchAliasSetter	produces (const TypeID &id, std::string instanceName=std::string(), bool recordProvenance=true)

template<BranchType B>
BranchAliasSetter	produces (const TypeID &id, std::string instanceName=std::string(), bool recordProvenance=true)

BranchAliasSetter	produces (const TypeID &id, std::string instanceName=std::string(), bool recordProvenance=true)

template<typename ProductType , Transition B>
BranchAliasSetterT< ProductType >	produces (std::string instanceName)

template<class ProductType >
BranchAliasSetterT< ProductType >	produces ()

template<typename ProductType , BranchType B>
BranchAliasSetterT< ProductType >	produces (std::string instanceName)

template<typename ProductType , BranchType B>
BranchAliasSetterT< ProductType >	produces ()

template<class ProductType >
BranchAliasSetterT< ProductType >	produces (std::string instanceName)

template<typename ProductType , Transition B>
BranchAliasSetterT< ProductType >	produces ()

template<Transition Tr = Transition::Event>
auto	produces () noexcept

ProducesCollector	producesCollector ()

Protected Member Functions inherited from edm::EDConsumerBase
template<typename ProductType , BranchType B = InEvent>
EDGetTokenT< ProductType >	consumes (edm::InputTag const &tag)

template<BranchType B = InEvent>
EDConsumerBaseAdaptor< B >	consumes (edm::InputTag tag) noexcept

EDGetToken	consumes (const TypeToGet &id, edm::InputTag const &tag)

template<BranchType B>
EDGetToken	consumes (TypeToGet const &id, edm::InputTag const &tag)

ConsumesCollector	consumesCollector ()
	Use a ConsumesCollector to gather consumes information from helper functions. More...

template<typename ESProduct , typename ESRecord , Transition Tr = Transition::Event>
auto	esConsumes ()

template<typename ESProduct , typename ESRecord , Transition Tr = Transition::Event>
auto	esConsumes (ESInputTag const &tag)

template<Transition Tr = Transition::Event>
constexpr auto	esConsumes ()

template<Transition Tr = Transition::Event>
auto	esConsumes (ESInputTag tag)

template<Transition Tr = Transition::Event>
ESGetTokenGeneric	esConsumes (eventsetup::EventSetupRecordKey const &iRecord, eventsetup::DataKey const &iKey)
	Used with EventSetupRecord::doGet. More...

template<typename ProductType , BranchType B = InEvent>
EDGetTokenT< ProductType >	mayConsume (edm::InputTag const &tag)

EDGetToken	mayConsume (const TypeToGet &id, edm::InputTag const &tag)

template<BranchType B>
EDGetToken	mayConsume (const TypeToGet &id, edm::InputTag const &tag)

void	resetItemsToGetFrom (BranchType iType)

Detailed Description

Create L3MuonTrajectorySeeds from L2 Muons in an outside-in manner.

Author: Dmitry Kondratyev, Arnab Purohit, Jan-Frederik Schulte (Purdue University, West Lafayette, USA)

Definition at line 40 of file TSGForOIDNN.cc.

Constructor & Destructor Documentation

◆ TSGForOIDNN()

TSGForOIDNN::TSGForOIDNN ( const edm::ParameterSet & iConfig )

explicit

Definition at line 181 of file TSGForOIDNN.cc.

References tensorflow::createSession(), HLT_2024v14_cff::dnnMetadataPath, dnnMetadataPath_, dnnModelPath_, dnnModelPath_HB_, dnnModelPath_HLIP_, dnnModelPath_HLMuS_, getStrategyFromDNN_, graphDef_, graphDef_HB_, graphDef_HLIP_, graphDef_HLMuS_, tensorflow::loadGraphDef(), metadata_, tensorflow::setLogging(), AlCaHLTBitMon_QueryRunRegistry::string, tf_session_, tf_session_HB_, tf_session_HLIP_, tf_session_HLMuS_, and useRegressor_.

     : src_(consumes(iConfig.getParameter<edm::InputTag>("src"))),
       t_estimatorH_(esConsumes(edm::ESInputTag("", iConfig.getParameter<std::string>("estimator")))),
       t_magfieldH_(esConsumes()),
       t_propagatorAlongH_(esConsumes(edm::ESInputTag("", iConfig.getParameter<std::string>("propagatorName")))),
       t_propagatorOppositeH_(esConsumes(edm::ESInputTag("", iConfig.getParameter<std::string>("propagatorName")))),
       t_tmpTkGeometryH_(esConsumes()),
       t_geometryH_(esConsumes()),
       t_navSchool_(esConsumes(edm::ESInputTag("", "SimpleNavigationSchool"))),
       t_SHPOpposite_(esConsumes(edm::ESInputTag("", "hltESPSteppingHelixPropagatorOpposite"))),
       updator_(new KFUpdator()),
       measurementTrackerTag_(consumes(iConfig.getParameter<edm::InputTag>("MeasurementTrackerEvent"))),
       theCategory_(std::string("Muon|RecoMuon|TSGForOIDNN")),
       maxSeeds_(iConfig.getParameter<uint32_t>("maxSeeds")),
       maxHitSeeds_(iConfig.getParameter<uint32_t>("maxHitSeeds")),
       maxHitlessSeeds_(iConfig.getParameter<uint32_t>("maxHitlessSeeds")),
       numOfLayersToTry_(iConfig.getParameter<int32_t>("layersToTry")),
       numOfHitsToTry_(iConfig.getParameter<int32_t>("hitsToTry")),
       fixedErrorRescalingForHitless_(iConfig.getParameter<double>("fixedErrorRescaleFactorForHitless")),
       minEtaForTEC_(iConfig.getParameter<double>("minEtaForTEC")),
       maxEtaForTOB_(iConfig.getParameter<double>("maxEtaForTOB")),
       maxHitlessSeedsIP_(iConfig.getParameter<uint32_t>("maxHitlessSeedsIP")),
       maxHitlessSeedsMuS_(iConfig.getParameter<uint32_t>("maxHitlessSeedsMuS")),
       maxHitDoubletSeeds_(iConfig.getParameter<uint32_t>("maxHitDoubletSeeds")),
       getStrategyFromDNN_(iConfig.getParameter<bool>("getStrategyFromDNN")),
       useRegressor_(iConfig.getParameter<bool>("useRegressor")),
       dnnMetadataPath_(iConfig.getParameter<std::string>("dnnMetadataPath")) {
   if (getStrategyFromDNN_) {
     edm::FileInPath dnnMetadataPath(dnnMetadataPath_);
     pt::read_json(dnnMetadataPath.fullPath(), metadata_);
     tensorflow::setLogging("3");
 
     if (useRegressor_) {
       // use regressor
       dnnModelPath_HB_ = metadata_.get<std::string>("HB.dnnmodel_path");
       edm::FileInPath dnnPath_HB(dnnModelPath_HB_);
       graphDef_HB_ = std::unique_ptr<tensorflow::GraphDef>(tensorflow::loadGraphDef(dnnPath_HB.fullPath()));
       tf_session_HB_ = tensorflow::createSession(graphDef_HB_.get());
 
       dnnModelPath_HLIP_ = metadata_.get<std::string>("HLIP.dnnmodel_path");
       edm::FileInPath dnnPath_HLIP(dnnModelPath_HLIP_);
       graphDef_HLIP_ = std::unique_ptr<tensorflow::GraphDef>(tensorflow::loadGraphDef(dnnPath_HLIP.fullPath()));
       tf_session_HLIP_ = tensorflow::createSession(graphDef_HLIP_.get());
 
       dnnModelPath_HLMuS_ = metadata_.get<std::string>("HLMuS.dnnmodel_path");
       edm::FileInPath dnnPath_HLMuS(dnnModelPath_HLMuS_);
       graphDef_HLMuS_ = std::unique_ptr<tensorflow::GraphDef>(tensorflow::loadGraphDef(dnnPath_HLMuS.fullPath()));
       tf_session_HLMuS_ = tensorflow::createSession(graphDef_HLMuS_.get());
     } else {
       // use classifier (default)
       dnnModelPath_ = metadata_.get<std::string>("dnnmodel_path");
       edm::FileInPath dnnPath(dnnModelPath_);
       graphDef_ = std::unique_ptr<tensorflow::GraphDef>(tensorflow::loadGraphDef(dnnPath.fullPath()));
       tf_session_ = tensorflow::createSession(graphDef_.get());
     }
   }
   produces<std::vector<TrajectorySeed> >();
 }

◆ ~TSGForOIDNN()

TSGForOIDNN::~TSGForOIDNN ( )

override

Definition at line 240 of file TSGForOIDNN.cc.

References tensorflow::closeSession(), getStrategyFromDNN_, tf_session_, tf_session_HB_, tf_session_HLIP_, tf_session_HLMuS_, and useRegressor_.

                           {
   if (getStrategyFromDNN_) {
     if (useRegressor_) {
       tensorflow::closeSession(tf_session_HB_);
       tensorflow::closeSession(tf_session_HLIP_);
       tensorflow::closeSession(tf_session_HLMuS_);
     } else {
       tensorflow::closeSession(tf_session_);
     }
   }
 }

Member Function Documentation

◆ beginJob()

void TSGForOIDNN::beginJob ( void )

overridevirtual

Reimplemented from edm::global::EDProducerBase.

Definition at line 252 of file TSGForOIDNN.cc.

References initializeTensorflow().

252 { initializeTensorflow(); }

TSGForOIDNN::initializeTensorflow

void initializeTensorflow() const

Definition: TSGForOIDNN.cc:287

◆ evaluateClassifier()

void TSGForOIDNN::evaluateClassifier	(	const std::unordered_map< std::string, float > &	feature_map,
		tensorflow::Session *	session,
		const pt::ptree &	metadata,
		StrategyParameters &	out,
		bool &	dnnSuccess
	)		const

private

Evaluate DNN classifier.

Definition at line 879 of file TSGForOIDNN.cc.

References nano_mu_digi_cff::float, alignmentValidation::fname, mps_fire::i, input, label, OccupancyTask_cfi::metadata, MillePedeFileConverter_cfg::out, PatBasicFWLiteJetAnalyzer_Selector_cfg::outputs, tensorflow::run(), AlCaHLTBitMon_QueryRunRegistry::string, and to_string().

Referenced by initializeTensorflow(), and produce().

                                                              {
   int n_features = metadata.get<int>("n_features", 0);
 
   // Prepare tensor for DNN inputs
   tensorflow::Tensor input(tensorflow::DT_FLOAT, {1, n_features});
   std::string fname;
   int i_feature = 0;
   for (const pt::ptree::value_type& feature : metadata.get_child("feature_names")) {
     fname = feature.second.data();
     if (feature_map.find(fname) == feature_map.end()) {
       // don't evaluate DNN if any input feature is missing
       dnnSuccess = false;
     } else {
       input.matrix<float>()(0, i_feature) = float(feature_map.at(fname));
       i_feature++;
     }
   }
 
   // Prepare tensor for DNN outputs
   std::vector<tensorflow::Tensor> outputs;
 
   // Evaluate DNN and put results in output tensor
   std::string inputLayer = metadata.get<std::string>("input_layer");
   std::string outputLayer = metadata.get<std::string>("output_layer");
 
   tensorflow::run(session, {{inputLayer, input}}, {outputLayer}, &outputs);
   tensorflow::Tensor out_tensor = outputs[0];
   tensorflow::TTypes<float, 1>::Matrix dnn_outputs = out_tensor.matrix<float>();
 
   // Find output with largest prediction
   int imax = 0;
   float out_max = 0;
   for (long long int i = 0; i < out_tensor.dim_size(1); i++) {
     float ith_output = dnn_outputs(0, i);
     if (ith_output > out_max) {
       imax = i;
       out_max = ith_output;
     }
   }
 
   // Decode output
   const std::string label = "output_labels.label_" + std::to_string(imax);
   out.nHBd = metadata.get<int>(label + ".nHBd");
   out.nHLIP = metadata.get<int>(label + ".nHLIP");
   out.nHLMuS = metadata.get<int>(label + ".nHLMuS");
   out.sf = metadata.get<int>(label + ".SF");
 
   dnnSuccess = true;
 }

◆ evaluateRegressor()

void TSGForOIDNN::evaluateRegressor	(	const std::unordered_map< std::string, float > &	feature_map,
		tensorflow::Session *	session_HB,
		const pt::ptree &	metadata_HB,
		tensorflow::Session *	session_HLIP,
		const pt::ptree &	metadata_HLIP,
		tensorflow::Session *	session_HLMuS,
		const pt::ptree &	metadata_HLMuS,
		StrategyParameters &	out,
		bool &	dnnSuccess
	)		const

private

Evaluate DNN regressor.

Definition at line 936 of file TSGForOIDNN.cc.

References nano_mu_digi_cff::float, alignmentValidation::fname, input, MillePedeFileConverter_cfg::out, tensorflow::run(), and AlCaHLTBitMon_QueryRunRegistry::string.

Referenced by produce().

                                                             {
   int n_features = metadata_HB.get<int>("n_features", 0);
 
   // Prepare tensor for DNN inputs
   tensorflow::Tensor input(tensorflow::DT_FLOAT, {1, n_features});
   std::string fname;
   int i_feature = 0;
   for (const pt::ptree::value_type& feature : metadata_HB.get_child("feature_names")) {
     fname = feature.second.data();
     if (feature_map.find(fname) == feature_map.end()) {
       // don't evaluate DNN if any input feature is missing
       dnnSuccess = false;
     } else {
       input.matrix<float>()(0, i_feature) = float(feature_map.at(fname));
       i_feature++;
     }
   }
 
   // Prepare tensor for DNN outputs
   std::vector<tensorflow::Tensor> outputs_HB;
   // Evaluate DNN and put results in output tensor
   std::string inputLayer_HB = metadata_HB.get<std::string>("input_layer");
   std::string outputLayer_HB = metadata_HB.get<std::string>("output_layer");
   tensorflow::run(session_HB, {{inputLayer_HB, input}}, {outputLayer_HB}, &outputs_HB);
   tensorflow::Tensor out_tensor_HB = outputs_HB[0];
   tensorflow::TTypes<float, 1>::Matrix dnn_outputs_HB = out_tensor_HB.matrix<float>();
 
   // Prepare tensor for DNN outputs
   std::vector<tensorflow::Tensor> outputs_HLIP;
   // Evaluate DNN and put results in output tensor
   std::string inputLayer_HLIP = metadata_HLIP.get<std::string>("input_layer");
   std::string outputLayer_HLIP = metadata_HLIP.get<std::string>("output_layer");
   tensorflow::run(session_HLIP, {{inputLayer_HLIP, input}}, {outputLayer_HLIP}, &outputs_HLIP);
   tensorflow::Tensor out_tensor_HLIP = outputs_HLIP[0];
   tensorflow::TTypes<float, 1>::Matrix dnn_outputs_HLIP = out_tensor_HLIP.matrix<float>();
 
   // Prepare tensor for DNN outputs
   std::vector<tensorflow::Tensor> outputs_HLMuS;
   // Evaluate DNN and put results in output tensor
   std::string inputLayer_HLMuS = metadata_HLMuS.get<std::string>("input_layer");
   std::string outputLayer_HLMuS = metadata_HLMuS.get<std::string>("output_layer");
   tensorflow::run(session_HLMuS, {{inputLayer_HLMuS, input}}, {outputLayer_HLMuS}, &outputs_HLMuS);
   tensorflow::Tensor out_tensor_HLMuS = outputs_HLMuS[0];
   tensorflow::TTypes<float, 1>::Matrix dnn_outputs_HLMuS = out_tensor_HLMuS.matrix<float>();
 
   // Decode output
   out.nHBd = round(dnn_outputs_HB(0, 0));
   out.nHLIP = round(dnn_outputs_HLIP(0, 0));
   out.sf = round(dnn_outputs_HLIP(0, 1));
   out.nHLMuS = round(dnn_outputs_HLMuS(0, 0));
 
   // Prevent prediction of negative number of seeds or too many seeds
   out.nHBd = std::clamp(out.nHBd, 0, 10);
   out.nHLIP = std::clamp(out.nHLIP, 0, 10);
   out.nHLMuS = std::clamp(out.nHLMuS, 0, 10);
 
   // Prevent prediction of 0 seeds in total
   if (out.nHBd == 0 && out.nHLIP == 0 && out.nHLMuS == 0) {
     // default strategy, similar to Run 2
     out.nHBd = 1;
     out.nHLIP = 5;
   }
 
   // Prevent extreme predictions for scale factors
   // (on average SF=2 was found to be optimal)
   if (out.sf <= 0)
     out.sf = 2;
   if (out.sf > 10)
     out.sf = 10;
 
   dnnSuccess = true;
 }

◆ fillDescriptions()

void TSGForOIDNN::fillDescriptions ( edm::ConfigurationDescriptions & descriptions )

static

Definition at line 1020 of file TSGForOIDNN.cc.

References edm::ConfigurationDescriptions::add(), submitPVResolutionJobs::desc, ProducerED_cfi::InputTag, and AlCaHLTBitMon_QueryRunRegistry::string.

                                                                              {
   edm::ParameterSetDescription desc;
   desc.add<edm::InputTag>("src", edm::InputTag("hltL2Muons", "UpdatedAtVtx"));
   desc.add<int>("layersToTry", 2);
   desc.add<double>("fixedErrorRescaleFactorForHitless", 2.0);
   desc.add<int>("hitsToTry", 1);
   desc.add<edm::InputTag>("MeasurementTrackerEvent", edm::InputTag("hltSiStripClusters"));
   desc.add<std::string>("estimator", "hltESPChi2MeasurementEstimator100");
   desc.add<double>("maxEtaForTOB", 1.8);
   desc.add<double>("minEtaForTEC", 0.7);
   desc.addUntracked<bool>("debug", false);
   desc.add<unsigned int>("maxSeeds", 20);
   desc.add<unsigned int>("maxHitlessSeeds", 5);
   desc.add<unsigned int>("maxHitSeeds", 1);
   desc.add<std::string>("propagatorName", "PropagatorWithMaterialParabolicMf");
   desc.add<unsigned int>("maxHitlessSeedsIP", 5);
   desc.add<unsigned int>("maxHitlessSeedsMuS", 0);
   desc.add<unsigned int>("maxHitDoubletSeeds", 0);
   desc.add<bool>("getStrategyFromDNN", false);
   desc.add<bool>("useRegressor", false);
   desc.add<std::string>("dnnMetadataPath", "");
   descriptions.add("tsgForOIDNN", desc);
 }

◆ initializeTensorflow()

void TSGForOIDNN::initializeTensorflow ( ) const

private

Definition at line 287 of file TSGForOIDNN.cc.

References evaluateClassifier(), getStrategyFromDNN_, metadata_, tf_session_, and useRegressor_.

Referenced by beginJob().

                                              {
   if (getStrategyFromDNN_ and not useRegressor_) {
     // Container for DNN outputs
     StrategyParameters strPars;
     bool dnnSuccess = false;
     evaluateClassifier(dummyFeatureMap(), tf_session_, metadata_, strPars, dnnSuccess);
   }
 }

◆ makeSeedsFromHitDoublets()

void TSGForOIDNN::makeSeedsFromHitDoublets	(	const GeometricSearchDet &	layer,
		const TrajectoryStateOnSurface &	tsos,
		const Propagator &	propagatorAlong,
		const Chi2MeasurementEstimatorBase &	estimator,
		const MeasurementTrackerEvent &	measurementTracker,
		const NavigationSchool &	navSchool,
		unsigned int &	hitDoubletSeedsMade,
		unsigned int &	numSeedsMade,
		const unsigned int &	maxHitDoubletSeeds,
		unsigned int &	layerCount,
		std::vector< TrajectorySeed > &	out
	)		const

private

Similar to makeSeedsFromHits, but seed is created only if there are compatible hits on two adjacent layers.

Definition at line 630 of file TSGForOIDNN.cc.

References alongMomentum, MeasurementDetWithData::fastMeasurements(), newFWLiteAna::found, TrajectoryStateOnSurface::freeState(), MeasurementDetWithData::isNull(), TrajectoryStateOnSurface::isValid(), nano_mu_digi_cff::layer, LogTrace, HLT_2024v14_cff::maxHitDoubletSeeds, HLTSiStripMonitoring_cff::measurementTracker, eostools::move(), HLT_2024v14_cff::navSchool, numOfHitsToTry_, oppositeToMomentum, MillePedeFileConverter_cfg::out, trajectoryStateTransform::persistentState(), L1TMuonDQMOffline_cfi::propagatorAlong, edm::OwnVector< T, P >::push_back(), fileCollector::seed, edm::OwnVector< T, P >::size(), jetUpdater_cfi::sort, and updator_.

Referenced by produce().

                                                                                  {
   // This method is similar to makeSeedsFromHits, but the seed is created
   // only when in addition to a hit on a given layer, there are more compatible hits
   // on next layers (going from outside inwards), compatible with updated TSOS.
   // If that's the case, multiple compatible hits are used to create a single seed.
 
   // Configured to only check the immideately adjacent layer and add one more hit
   int max_addtnl_layers = 1;  // max number of additional layers to scan
   int max_meas = 1;           // number of measurements to consider on each additional layer
 
   // // // First, regular procedure to find a compatible hit - like in makeSeedsFromHits // // //
 
   const TrajectoryStateOnSurface& onLayer(tsos);
 
   // Find dets compatible with original TSOS
   std::vector<GeometricSearchDet::DetWithState> dets;
   layer.compatibleDetsV(onLayer, propagatorAlong, estimator, dets);
 
   LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsFromHitDoublets: Find measurements on each detWithState  "
                           << dets.size();
   std::vector<TrajectoryMeasurement> meas;
 
   // Loop over dets
   for (auto const& detI : dets) {
     MeasurementDetWithData det = measurementTracker.idToDet(detI.first->geographicalId());
 
     if (det.isNull())
       continue;  // skip if det does not exist
     if (!detI.second.isValid())
       continue;  // skip if TSOS is invalid
 
     // Find measurements on this det
     std::vector<TrajectoryMeasurement> mymeas = det.fastMeasurements(detI.second, onLayer, propagatorAlong, estimator);
 
     // Save valid measurements
     for (auto const& measurement : mymeas) {
       if (measurement.recHit()->isValid())
         meas.push_back(measurement);
     }  // end loop over meas
   }    // end loop over dets
 
   LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsFromHitDoublets: Update TSOS using TMs after sorting, then create "
                              "Trajectory Seed, number of TM = "
                           << meas.size();
 
   // sort valid measurements found on the first layer
   std::sort(meas.begin(), meas.end(), TrajMeasLessEstim());
 
   unsigned int found = 0;
 
   // Loop over all valid measurements compatible with original TSOS
   //for (std::vector<TrajectoryMeasurement>::const_iterator mea = meas.begin(); mea != meas.end(); ++mea) {
   for (auto const& measurement : meas) {
     if (hitDoubletSeedsMade >= maxHitDoubletSeeds)
       return;  // abort if enough seeds created
 
     // Update TSOS with measurement on first considered layer
     TrajectoryStateOnSurface updatedTSOS = updator_->update(measurement.forwardPredictedState(), *measurement.recHit());
 
     LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsFromHitDoublets: TSOS for TM " << found;
     if (not updatedTSOS.isValid())
       continue;  // Skip if updated TSOS is invalid
 
     edm::OwnVector<TrackingRecHit> seedHits;
 
     // Save hit on first layer
     seedHits.push_back(*measurement.recHit()->hit());
     const DetLayer* detLayer = dynamic_cast<const DetLayer*>(&layer);
 
     // // // Now for this measurement we will loop over additional layers and try to update the TSOS again // // //
 
     // find layers compatible with updated TSOS
     auto const& compLayers = navSchool.nextLayers(*detLayer, *updatedTSOS.freeState(), alongMomentum);
 
     int addtnl_layers_scanned = 0;
     int found_compatible_on_next_layer = 0;
     int det_id = 0;
 
     // Copy updated TSOS - we will update it again with a measurement from the next layer, if we find it
     TrajectoryStateOnSurface updatedTSOS_next(updatedTSOS);
 
     // loop over layers compatible with updated TSOS
     for (auto compLayer : compLayers) {
       int nmeas = 0;
 
       if (addtnl_layers_scanned >= max_addtnl_layers)
         break;  // break if we already looped over enough layers
       if (found_compatible_on_next_layer > 0)
         break;  // break if we already found additional hit
 
       // find dets compatible with updated TSOS
       std::vector<GeometricSearchDet::DetWithState> dets_next;
       TrajectoryStateOnSurface onLayer_next(updatedTSOS);
 
       compLayer->compatibleDetsV(onLayer_next, propagatorAlong, estimator, dets_next);
 
       //if (!detWithState.size()) continue;
       std::vector<TrajectoryMeasurement> meas_next;
 
       // find measurements on dets_next and save the valid ones
       for (auto const& detI_next : dets_next) {
         MeasurementDetWithData det = measurementTracker.idToDet(detI_next.first->geographicalId());
 
         if (det.isNull())
           continue;  // skip if det does not exist
         if (!detI_next.second.isValid())
           continue;  // skip if TSOS is invalid
 
         // Find measurements on this det
         std::vector<TrajectoryMeasurement> mymeas_next =
             det.fastMeasurements(detI_next.second, onLayer_next, propagatorAlong, estimator);
 
         for (auto const& mea_next : mymeas_next) {
           // save valid measurements
           if (mea_next.recHit()->isValid())
             meas_next.push_back(mea_next);
 
         }  // end loop over mymeas_next
       }    // end loop over dets_next
 
       // sort valid measurements found on this layer
       std::sort(meas_next.begin(), meas_next.end(), TrajMeasLessEstim());
 
       // loop over valid measurements compatible with updated TSOS (TSOS updated with a hit on the first layer)
       for (auto const& mea_next : meas_next) {
         if (nmeas >= max_meas)
           break;  // skip if we already found enough hits
 
         // try to update TSOS again, with an additional hit
         updatedTSOS_next = updator_->update(mea_next.forwardPredictedState(), *mea_next.recHit());
 
         if (not updatedTSOS_next.isValid())
           continue;  // skip if TSOS updated with additional hit is not valid
 
         // If there was a compatible hit on this layer, we end up here.
         // An additional compatible hit is saved.
         seedHits.push_back(*mea_next.recHit()->hit());
         det_id = mea_next.recHit()->geographicalId().rawId();
         nmeas++;
         found_compatible_on_next_layer++;
 
       }  // end loop over meas_next
 
       addtnl_layers_scanned++;
 
     }  // end loop over compLayers (additional layers scanned after the original layer)
 
     if (found_compatible_on_next_layer == 0)
       continue;
     // only consider the hit if there was a compatible hit on one of the additional scanned layers
 
     // Create a seed from two saved hits
     PTrajectoryStateOnDet const& pstate = trajectoryStateTransform::persistentState(updatedTSOS_next, det_id);
     TrajectorySeed seed(pstate, std::move(seedHits), oppositeToMomentum);
 
     LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsFromHitDoublets: Number of seedHits: " << seedHits.size();
     out.push_back(seed);
 
     found++;
     numSeedsMade++;
     hitDoubletSeedsMade++;
 
     if (found == numOfHitsToTry_)
       break;  // break if enough measurements scanned
 
   }  // end loop over measurements compatible with original TSOS
 
   if (found)
     layerCount++;
 }

◆ makeSeedsFromHits()

void TSGForOIDNN::makeSeedsFromHits	(	const GeometricSearchDet &	layer,
		const TrajectoryStateOnSurface &	tsos,
		const Propagator &	propagatorAlong,
		const Chi2MeasurementEstimatorBase &	estimator,
		const MeasurementTrackerEvent &	measurementTracker,
		unsigned int &	hitSeedsMade,
		unsigned int &	numSeedsMade,
		const unsigned int &	maxHitSeeds,
		unsigned int &	layerCount,
		std::vector< TrajectorySeed > &	out
	)		const

private

Find hits on a given layer (TOB or TEC) and create seeds from updated TSOS with hit.

Definition at line 558 of file TSGForOIDNN.cc.

References MeasurementDetWithData::fastMeasurements(), newFWLiteAna::found, MeasurementDetWithData::isNull(), TrajectoryStateOnSurface::isValid(), nano_mu_digi_cff::layer, LogTrace, HLT_2024v14_cff::maxHitSeeds, HLTSiStripMonitoring_cff::measurementTracker, eostools::move(), numOfHitsToTry_, numOfLayersToTry_, oppositeToMomentum, MillePedeFileConverter_cfg::out, trajectoryStateTransform::persistentState(), L1TMuonDQMOffline_cfi::propagatorAlong, edm::OwnVector< T, P >::push_back(), fileCollector::seed, edm::OwnVector< T, P >::size(), jetUpdater_cfi::sort, and updator_.

Referenced by produce().

                                                                           {
   if (layerCount > numOfLayersToTry_)
     return;
 
   const TrajectoryStateOnSurface& onLayer(tsos);
 
   std::vector<GeometricSearchDet::DetWithState> dets;
   layer.compatibleDetsV(onLayer, propagatorAlong, estimator, dets);
 
   // Find Measurements on each DetWithState
   LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsFromHits: Find measurements on each detWithState  " << dets.size();
   std::vector<TrajectoryMeasurement> meas;
   for (auto const& detI : dets) {
     MeasurementDetWithData det = measurementTracker.idToDet(detI.first->geographicalId());
     if (det.isNull())
       continue;
     if (!detI.second.isValid())
       continue;  // Skip if TSOS is not valid
 
     std::vector<TrajectoryMeasurement> mymeas =
         det.fastMeasurements(detI.second, onLayer, propagatorAlong, estimator);  // Second TSOS is not used
     for (auto const& measurement : mymeas) {
       if (measurement.recHit()->isValid())
         meas.push_back(measurement);  // Only save those which are valid
     }
   }
 
   // Update TSOS using TMs after sorting, then create Trajectory Seed and put into vector
   LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsFromHits: Update TSOS using TMs after sorting, then create "
                              "Trajectory Seed, number of TM = "
                           << meas.size();
   std::sort(meas.begin(), meas.end(), TrajMeasLessEstim());
 
   unsigned int found = 0;
   for (auto const& measurement : meas) {
     if (hitSeedsMade >= maxHitSeeds)
       return;
     TrajectoryStateOnSurface updatedTSOS = updator_->update(measurement.forwardPredictedState(), *measurement.recHit());
     LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsFromHits: TSOS for TM " << found;
     if (not updatedTSOS.isValid())
       continue;
 
     edm::OwnVector<TrackingRecHit> seedHits;
     seedHits.push_back(*measurement.recHit()->hit());
     PTrajectoryStateOnDet const& pstate =
         trajectoryStateTransform::persistentState(updatedTSOS, measurement.recHit()->geographicalId().rawId());
     LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsFromHits: Number of seedHits: " << seedHits.size();
     TrajectorySeed seed(pstate, std::move(seedHits), oppositeToMomentum);
     out.push_back(seed);
     found++;
     numSeedsMade++;
     hitSeedsMade++;
     if (found == numOfHitsToTry_)
       break;
   }
 
   if (found)
     layerCount++;
 }

◆ makeSeedsWithoutHits()

void TSGForOIDNN::makeSeedsWithoutHits	(	const GeometricSearchDet &	layer,
		const TrajectoryStateOnSurface &	tsos,
		const Propagator &	propagatorAlong,
		const Chi2MeasurementEstimatorBase &	estimator,
		double	errorSF,
		unsigned int &	hitlessSeedsMade,
		unsigned int &	numSeedsMade,
		std::vector< TrajectorySeed > &	out
	)		const

private

Create seeds without hits on a given layer (TOB or TEC)

Definition at line 524 of file TSGForOIDNN.cc.

References nano_mu_digi_cff::layer, LogTrace, oppositeToMomentum, MillePedeFileConverter_cfg::out, trajectoryStateTransform::persistentState(), L1TMuonDQMOffline_cfi::propagatorAlong, and theCategory_.

Referenced by produce().

                                                                              {
   // create hitless seeds
   LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsWithoutHits: Start hitless";
   std::vector<GeometricSearchDet::DetWithState> dets;
   layer.compatibleDetsV(tsos, propagatorAlong, estimator, dets);
   if (!dets.empty()) {
     auto const& detOnLayer = dets.front().first;
     auto& tsosOnLayer = dets.front().second;
     LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsWithoutHits: tsosOnLayer " << tsosOnLayer;
     if (!tsosOnLayer.isValid()) {
       edm::LogInfo(theCategory_) << "ERROR!: Hitless TSOS is not valid!";
     } else {
       tsosOnLayer.rescaleError(errorSF);
       PTrajectoryStateOnDet const& ptsod =
           trajectoryStateTransform::persistentState(tsosOnLayer, detOnLayer->geographicalId().rawId());
       TrajectorySeed::RecHitContainer rHC;
       out.push_back(TrajectorySeed(ptsod, rHC, oppositeToMomentum));
       LogTrace("TSGForOIDNN") << "TSGForOIDNN::makeSeedsWithoutHits: TSOS (Hitless) done ";
       hitlessSeedsMade++;
       numSeedsMade++;
     }
   }
 }

◆ produce()

void TSGForOIDNN::produce	(	edm::StreamID	sid,
		edm::Event &	iEvent,
		const edm::EventSetup &	iSetup
	)		const

overridevirtual

Implements edm::global::EDProducerBase.

Definition at line 299 of file TSGForOIDNN.cc.

References funct::abs(), alongMomentum, Plane::build(), evaluateClassifier(), evaluateRegressor(), fixedErrorRescalingForHitless_, edm::EventSetup::getData(), edm::EventSetup::getHandle(), getStrategyFromDNN_, iEvent, trajectoryStateTransform::initialFreeState(), trajectoryStateTransform::innerStateOnSurface(), TrackerGeometry::isThere(), TrajectoryStateOnSurface::isValid(), ALPAKA_ACCELERATOR_NAMESPACE::vertexFinder::it, HLTObjectMonitor_cfi::l2muonEta, nano_mu_digi_cff::layer, hgcalTBTopologyTester_cfi::layers, LogTrace, volumeBasedMagneticField_160812_cfi::magfield, makeSeedsFromHitDoublets(), makeSeedsFromHits(), makeSeedsWithoutHits(), maxEtaForTOB_, HLT_2024v14_cff::maxHitDoubletSeeds, maxHitDoubletSeeds_, HLT_2024v14_cff::maxHitlessSeedsIP, maxHitlessSeedsIP_, HLT_2024v14_cff::maxHitlessSeedsMuS, maxHitlessSeedsMuS_, HLT_2024v14_cff::maxHitSeeds, maxHitSeeds_, maxSeeds_, HLTSiStripMonitoring_cff::measurementTracker, measurementTrackerTag_, metadata_, minEtaForTEC_, eostools::move(), HLT_2024v14_cff::navSchool, TSGForOIDNN::StrategyParameters::nHBd, TSGForOIDNN::StrategyParameters::nHLIP, TSGForOIDNN::StrategyParameters::nHLMuS, oppositeToMomentum, MillePedeFileConverter_cfg::out, GeomDetEnumerators::P2OTEC, FreeTrajectoryState::position(), L1TMuonDQMOffline_cfi::propagatorAlong, L1TMuonDQMOffline_cfi::propagatorOpposite, mps_fire::result, groupFilesInBlocks::reverse, SetPropagationDirection(), TSGForOIDNN::StrategyParameters::sf, src_, t_estimatorH_, t_geometryH_, t_magfieldH_, t_navSchool_, t_propagatorAlongH_, t_propagatorOppositeH_, t_SHPOpposite_, t_tmpTkGeometryH_, tf_session_, tf_session_HB_, tf_session_HLIP_, tf_session_HLMuS_, theCategory_, updateFeatureMap(), and useRegressor_.

                                                                                                    {
   // Initialize variables
   unsigned int numSeedsMade = 0;
   unsigned int layerCount = 0;
   unsigned int hitlessSeedsMadeIP = 0;
   unsigned int hitlessSeedsMadeMuS = 0;
   unsigned int hitSeedsMade = 0;
   unsigned int hitDoubletSeedsMade = 0;
 
   // Container for DNN inputs
   std::unordered_map<std::string, float> feature_map;
 
   // Container for DNN outputs
   StrategyParameters strPars;
 
   // Surface used to make a TSOS at the PCA to the beamline
   Plane::PlanePointer dummyPlane = Plane::build(Plane::PositionType(), Plane::RotationType());
 
   // Get setup objects
   const MagneticField& magfield = iEventSetup.getData(t_magfieldH_);
   const Chi2MeasurementEstimatorBase& estimator = iEventSetup.getData(t_estimatorH_);
   const Propagator& tmpPropagatorAlong = iEventSetup.getData(t_propagatorAlongH_);
   const Propagator& tmpPropagatorOpposite = iEventSetup.getData(t_propagatorOppositeH_);
   const TrackerGeometry& tmpTkGeometry = iEventSetup.getData(t_tmpTkGeometryH_);
   const GlobalTrackingGeometry& geometry = iEventSetup.getData(t_geometryH_);
   const NavigationSchool& navSchool = iEventSetup.getData(t_navSchool_);
   auto const& measurementTracker = iEvent.get(measurementTrackerTag_);
 
   // Read L2 track collection
   auto const& l2TrackCol = iEvent.get(src_);
 
   // The product
   std::unique_ptr<std::vector<TrajectorySeed> > result(new std::vector<TrajectorySeed>());
 
   // Get vector of Detector layers
   auto const* gsTracker = measurementTracker.geometricSearchTracker();
   std::vector<BarrelDetLayer const*> const& tob = gsTracker->tobLayers();
   std::vector<ForwardDetLayer const*> const& tecPositive =
       tmpTkGeometry.isThere(GeomDetEnumerators::P2OTEC) ? gsTracker->posTidLayers() : gsTracker->posTecLayers();
   std::vector<ForwardDetLayer const*> const& tecNegative =
       tmpTkGeometry.isThere(GeomDetEnumerators::P2OTEC) ? gsTracker->negTidLayers() : gsTracker->negTecLayers();
 
   // Get suitable propagators
   std::unique_ptr<Propagator> propagatorAlong = SetPropagationDirection(tmpPropagatorAlong, alongMomentum);
   std::unique_ptr<Propagator> propagatorOpposite = SetPropagationDirection(tmpPropagatorOpposite, oppositeToMomentum);
 
   // Stepping Helix Propagator for propogation from muon system to tracker
   edm::ESHandle<Propagator> shpOpposite = iEventSetup.getHandle(t_SHPOpposite_);
 
   // Loop over the L2's and make seeds for all of them
   LogTrace(theCategory_) << "TSGForOIDNN::produce: Number of L2's: " << l2TrackCol.size();
 
   for (auto const& l2 : l2TrackCol) {
     // Container of Seeds
     std::vector<TrajectorySeed> out;
     LogTrace("TSGForOIDNN") << "TSGForOIDNN::produce: L2 muon pT, eta, phi --> " << l2.pt() << " , " << l2.eta()
                             << " , " << l2.phi();
 
     FreeTrajectoryState fts = trajectoryStateTransform::initialFreeState(l2, &magfield);
 
     dummyPlane->move(fts.position() - dummyPlane->position());
     TrajectoryStateOnSurface tsosAtIP = TrajectoryStateOnSurface(fts, *dummyPlane);
     LogTrace("TSGForOIDNN") << "TSGForOIDNN::produce: Created TSOSatIP: " << tsosAtIP;
 
     // Get the TSOS on the innermost layer of the L2
     TrajectoryStateOnSurface tsosAtMuonSystem = trajectoryStateTransform::innerStateOnSurface(l2, geometry, &magfield);
     LogTrace("TSGForOIDNN") << "TSGForOIDNN::produce: Created TSOSatMuonSystem: " << tsosAtMuonSystem;
 
     LogTrace("TSGForOIDNN")
         << "TSGForOIDNN::produce: Check the error of the L2 parameter and use hit seeds if big errors";
 
     StateOnTrackerBound fromInside(propagatorAlong.get());
     TrajectoryStateOnSurface outerTkStateInside = fromInside(fts);
 
     StateOnTrackerBound fromOutside(&*shpOpposite);
     TrajectoryStateOnSurface outerTkStateOutside = fromOutside(tsosAtMuonSystem);
 
     // Check if the two positions (using updated and not-updated TSOS) agree withing certain extent.
     // If both TSOSs agree, use only the one at vertex, as it uses more information. If they do not agree, search for seeds based on both.
     double l2muonEta = l2.eta();
     double absL2muonEta = std::abs(l2muonEta);
 
     // make non-const copies of parameters, so they can be overriden for individual L2 muons
     unsigned int maxHitSeeds = maxHitSeeds_;
     unsigned int maxHitDoubletSeeds = maxHitDoubletSeeds_;
     unsigned int maxHitlessSeedsIP = maxHitlessSeedsIP_;
     unsigned int maxHitlessSeedsMuS = maxHitlessSeedsMuS_;
 
     float errorSFHitless = fixedErrorRescalingForHitless_;
 
     // update strategy parameters by evaluating DNN
     if (getStrategyFromDNN_) {
       bool dnnSuccess = false;
 
       // Update feature map with parameters of the current muon
       updateFeatureMap(feature_map, l2, tsosAtIP, outerTkStateOutside);
 
       if (useRegressor_) {
         // Use regressor
         evaluateRegressor(feature_map,
                           tf_session_HB_,
                           metadata_.get_child("HB"),
                           tf_session_HLIP_,
                           metadata_.get_child("HLIP"),
                           tf_session_HLMuS_,
                           metadata_.get_child("HLMuS"),
                           strPars,
                           dnnSuccess);
       } else {
         // Use classifier
         evaluateClassifier(feature_map, tf_session_, metadata_, strPars, dnnSuccess);
       }
       if (!dnnSuccess)
         break;
 
       maxHitSeeds = 0;
       maxHitDoubletSeeds = strPars.nHBd;
       maxHitlessSeedsIP = strPars.nHLIP;
       maxHitlessSeedsMuS = strPars.nHLMuS;
       errorSFHitless = strPars.sf;
     }
 
     numSeedsMade = 0;
     hitlessSeedsMadeIP = 0;
     hitlessSeedsMadeMuS = 0;
     hitSeedsMade = 0;
     hitDoubletSeedsMade = 0;
 
     auto createSeeds = [&](auto const& layers) {
       for (auto const& layer : boost::adaptors::reverse(layers)) {
         if (hitlessSeedsMadeIP < maxHitlessSeedsIP && numSeedsMade < maxSeeds_)
           makeSeedsWithoutHits(*layer,
                                tsosAtIP,
                                *(propagatorAlong.get()),
                                estimator,
                                errorSFHitless,
                                hitlessSeedsMadeIP,
                                numSeedsMade,
                                out);
 
         if (outerTkStateInside.isValid() && outerTkStateOutside.isValid() && hitlessSeedsMadeMuS < maxHitlessSeedsMuS &&
             numSeedsMade < maxSeeds_)
           makeSeedsWithoutHits(*layer,
                                outerTkStateOutside,
                                *(propagatorOpposite.get()),
                                estimator,
                                errorSFHitless,
                                hitlessSeedsMadeMuS,
                                numSeedsMade,
                                out);
 
         if (hitSeedsMade < maxHitSeeds && numSeedsMade < maxSeeds_)
           makeSeedsFromHits(*layer,
                             tsosAtIP,
                             *(propagatorAlong.get()),
                             estimator,
                             measurementTracker,
                             hitSeedsMade,
                             numSeedsMade,
                             maxHitSeeds,
                             layerCount,
                             out);
 
         if (hitDoubletSeedsMade < maxHitDoubletSeeds && numSeedsMade < maxSeeds_)
           makeSeedsFromHitDoublets(*layer,
                                    tsosAtIP,
                                    *(propagatorAlong.get()),
                                    estimator,
                                    measurementTracker,
                                    navSchool,
                                    hitDoubletSeedsMade,
                                    numSeedsMade,
                                    maxHitDoubletSeeds,
                                    layerCount,
                                    out);
       };
     };
 
     // BARREL
     if (absL2muonEta < maxEtaForTOB_) {
       layerCount = 0;
       createSeeds(tob);
       LogTrace("TSGForOIDNN") << "TSGForOIDNN:::produce: NumSeedsMade = " << numSeedsMade
                               << " , layerCount = " << layerCount;
     }
 
     // Reset number of seeds if in overlap region
     if (absL2muonEta > minEtaForTEC_ && absL2muonEta < maxEtaForTOB_) {
       numSeedsMade = 0;
       hitlessSeedsMadeIP = 0;
       hitlessSeedsMadeMuS = 0;
       hitSeedsMade = 0;
       hitDoubletSeedsMade = 0;
     }
 
     // ENDCAP+
     if (l2muonEta > minEtaForTEC_) {
       layerCount = 0;
       createSeeds(tecPositive);
       LogTrace("TSGForOIDNN") << "TSGForOIDNN:::produce: NumSeedsMade = " << numSeedsMade
                               << " , layerCount = " << layerCount;
     }
 
     // ENDCAP-
     if (l2muonEta < -minEtaForTEC_) {
       layerCount = 0;
       createSeeds(tecNegative);
       LogTrace("TSGForOIDNN") << "TSGForOIDNN:::produce: NumSeedsMade = " << numSeedsMade
                               << " , layerCount = " << layerCount;
     }
 
     for (std::vector<TrajectorySeed>::iterator it = out.begin(); it != out.end(); ++it) {
       result->push_back(*it);
     }
 
   }  // L2Collection
 
   edm::LogInfo(theCategory_) << "TSGForOIDNN::produce: number of seeds made: " << result->size();
 
   iEvent.put(std::move(result));
 }

◆ updateFeatureMap()

void TSGForOIDNN::updateFeatureMap	(	std::unordered_map< std::string, float > &	the_map,
		const reco::Track &	l2,
		const TrajectoryStateOnSurface &	tsos_IP,
		const TrajectoryStateOnSurface &	tsos_MuS
	)		const

private

Update dictionary of inputs for DNN.

Definition at line 814 of file TSGForOIDNN.cc.

References TrajectoryStateOnSurface::curvilinearError(), PV3DBase< T, PVType, FrameType >::eta(), reco::TrackBase::eta(), reco::Track::found(), TrajectoryStateOnSurface::globalMomentum(), TrajectoryStateOnSurface::globalPosition(), TrajectoryStateOnSurface::isValid(), CurvilinearTrajectoryError::matrix(), PV3DBase< T, PVType, FrameType >::perp(), PV3DBase< T, PVType, FrameType >::phi(), reco::TrackBase::phi(), reco::TrackBase::pt(), and mathSSE::sqrt().

Referenced by produce().

                                                                                    {
   the_map["pt"] = l2.pt();
   the_map["eta"] = l2.eta();
   the_map["phi"] = l2.phi();
   the_map["validHits"] = l2.found();
   if (tsos_IP.isValid()) {
     the_map["tsos_IP_eta"] = tsos_IP.globalPosition().eta();
     the_map["tsos_IP_phi"] = tsos_IP.globalPosition().phi();
     the_map["tsos_IP_pt"] = tsos_IP.globalMomentum().perp();
     the_map["tsos_IP_pt_eta"] = tsos_IP.globalMomentum().eta();
     the_map["tsos_IP_pt_phi"] = tsos_IP.globalMomentum().phi();
     const AlgebraicSymMatrix55& matrix_IP = tsos_IP.curvilinearError().matrix();
     the_map["err0_IP"] = sqrt(matrix_IP[0][0]);
     the_map["err1_IP"] = sqrt(matrix_IP[1][1]);
     the_map["err2_IP"] = sqrt(matrix_IP[2][2]);
     the_map["err3_IP"] = sqrt(matrix_IP[3][3]);
     the_map["err4_IP"] = sqrt(matrix_IP[4][4]);
     the_map["tsos_IP_valid"] = 1.0;
   } else {
     the_map["tsos_IP_eta"] = -999;
     the_map["tsos_IP_phi"] = -999;
     the_map["tsos_IP_pt"] = -999;
     the_map["tsos_IP_pt_eta"] = -999;
     the_map["tsos_IP_pt_phi"] = -999;
     the_map["err0_IP"] = -999;
     the_map["err1_IP"] = -999;
     the_map["err2_IP"] = -999;
     the_map["err3_IP"] = -999;
     the_map["err4_IP"] = -999;
     the_map["tsos_IP_valid"] = 0.0;
   }
   if (tsos_MuS.isValid()) {
     the_map["tsos_MuS_eta"] = tsos_MuS.globalPosition().eta();
     the_map["tsos_MuS_phi"] = tsos_MuS.globalPosition().phi();
     the_map["tsos_MuS_pt"] = tsos_MuS.globalMomentum().perp();
     the_map["tsos_MuS_pt_eta"] = tsos_MuS.globalMomentum().eta();
     the_map["tsos_MuS_pt_phi"] = tsos_MuS.globalMomentum().phi();
     const AlgebraicSymMatrix55& matrix_MuS = tsos_MuS.curvilinearError().matrix();
     the_map["err0_MuS"] = sqrt(matrix_MuS[0][0]);
     the_map["err1_MuS"] = sqrt(matrix_MuS[1][1]);
     the_map["err2_MuS"] = sqrt(matrix_MuS[2][2]);
     the_map["err3_MuS"] = sqrt(matrix_MuS[3][3]);
     the_map["err4_MuS"] = sqrt(matrix_MuS[4][4]);
     the_map["tsos_MuS_valid"] = 1.0;
   } else {
     the_map["tsos_MuS_eta"] = -999;
     the_map["tsos_MuS_phi"] = -999;
     the_map["tsos_MuS_pt"] = -999;
     the_map["tsos_MuS_pt_eta"] = -999;
     the_map["tsos_MuS_pt_phi"] = -999;
     the_map["err0_MuS"] = -999;
     the_map["err1_MuS"] = -999;
     the_map["err2_MuS"] = -999;
     the_map["err3_MuS"] = -999;
     the_map["err4_MuS"] = -999;
     the_map["tsos_MuS_valid"] = 0.0;
   }
 }

Member Data Documentation

◆ dnnMetadataPath_

const std::string TSGForOIDNN::dnnMetadataPath_

private

DNN metadata.

Definition at line 111 of file TSGForOIDNN.cc.

Referenced by TSGForOIDNN().

◆ dnnModelPath_

std::string TSGForOIDNN::dnnModelPath_

private

Settings for classifier.

Definition at line 95 of file TSGForOIDNN.cc.

Referenced by TSGForOIDNN().

◆ dnnModelPath_HB_

std::string TSGForOIDNN::dnnModelPath_HB_

private

Settings for regressor.

Definition at line 100 of file TSGForOIDNN.cc.

Referenced by TSGForOIDNN().

◆ dnnModelPath_HLIP_

std::string TSGForOIDNN::dnnModelPath_HLIP_

private

Definition at line 101 of file TSGForOIDNN.cc.

Referenced by TSGForOIDNN().

◆ dnnModelPath_HLMuS_

std::string TSGForOIDNN::dnnModelPath_HLMuS_

private

Definition at line 102 of file TSGForOIDNN.cc.

Referenced by TSGForOIDNN().

◆ estimatorName_

const std::string TSGForOIDNN::estimatorName_

private

Estimator used to find dets and TrajectoryMeasurements.

Definition at line 77 of file TSGForOIDNN.cc.

◆ fixedErrorRescalingForHitless_

const double TSGForOIDNN::fixedErrorRescalingForHitless_

private

Rescale L2 parameter uncertainties (fixed error vs pT, eta)

Definition at line 75 of file TSGForOIDNN.cc.

Referenced by produce().

◆ getStrategyFromDNN_

const bool TSGForOIDNN::getStrategyFromDNN_

private

Get number of seeds to use from DNN output instead of "max..Seeds" parameters.

Definition at line 90 of file TSGForOIDNN.cc.

Referenced by initializeTensorflow(), produce(), TSGForOIDNN(), and ~TSGForOIDNN().

◆ graphDef_

std::unique_ptr<tensorflow::GraphDef> TSGForOIDNN::graphDef_

private

Definition at line 96 of file TSGForOIDNN.cc.

Referenced by TSGForOIDNN().

◆ graphDef_HB_

std::unique_ptr<tensorflow::GraphDef> TSGForOIDNN::graphDef_HB_

private

Definition at line 103 of file TSGForOIDNN.cc.

Referenced by TSGForOIDNN().

◆ graphDef_HLIP_

std::unique_ptr<tensorflow::GraphDef> TSGForOIDNN::graphDef_HLIP_

private

Definition at line 105 of file TSGForOIDNN.cc.

Referenced by TSGForOIDNN().

◆ graphDef_HLMuS_

std::unique_ptr<tensorflow::GraphDef> TSGForOIDNN::graphDef_HLMuS_

private

Definition at line 107 of file TSGForOIDNN.cc.

Referenced by TSGForOIDNN().

◆ maxEtaForTOB_

const double TSGForOIDNN::maxEtaForTOB_

private

Maximum eta value to activate searching in the TOB.

Definition at line 81 of file TSGForOIDNN.cc.

Referenced by produce().

◆ maxHitDoubletSeeds_

const unsigned int TSGForOIDNN::maxHitDoubletSeeds_

private

Definition at line 87 of file TSGForOIDNN.cc.

Referenced by produce().

◆ maxHitlessSeeds_

const unsigned int TSGForOIDNN::maxHitlessSeeds_

private

Maximum number of hitless seeds for each L2.

Definition at line 69 of file TSGForOIDNN.cc.

◆ maxHitlessSeedsIP_

const unsigned int TSGForOIDNN::maxHitlessSeedsIP_

private

IP refers to TSOS at interaction point, MuS refers to TSOS at muon system

Definition at line 85 of file TSGForOIDNN.cc.

Referenced by produce().

◆ maxHitlessSeedsMuS_

const unsigned int TSGForOIDNN::maxHitlessSeedsMuS_

private

Definition at line 86 of file TSGForOIDNN.cc.

Referenced by produce().

◆ maxHitSeeds_

const unsigned int TSGForOIDNN::maxHitSeeds_

private

Maximum number of hitbased seeds for each L2.

Definition at line 67 of file TSGForOIDNN.cc.

Referenced by produce().

◆ maxSeeds_

const unsigned int TSGForOIDNN::maxSeeds_

private

Maximum number of seeds for each L2.

Definition at line 65 of file TSGForOIDNN.cc.

Referenced by produce().

◆ measurementTrackerTag_

const edm::EDGetTokenT<MeasurementTrackerEvent> TSGForOIDNN::measurementTrackerTag_

private

Definition at line 61 of file TSGForOIDNN.cc.

Referenced by produce().

◆ metadata_

pt::ptree TSGForOIDNN::metadata_

private

Definition at line 112 of file TSGForOIDNN.cc.

Referenced by initializeTensorflow(), produce(), and TSGForOIDNN().

◆ minEtaForTEC_

const double TSGForOIDNN::minEtaForTEC_

private

Minimum eta value to activate searching in the TEC.

Definition at line 79 of file TSGForOIDNN.cc.

Referenced by produce().

◆ numOfHitsToTry_

const unsigned int TSGForOIDNN::numOfHitsToTry_

private

How many hits to try per layer.

Definition at line 73 of file TSGForOIDNN.cc.

Referenced by makeSeedsFromHitDoublets(), and makeSeedsFromHits().

◆ numOfLayersToTry_

const unsigned int TSGForOIDNN::numOfLayersToTry_

private

How many layers to try.

Definition at line 71 of file TSGForOIDNN.cc.

Referenced by makeSeedsFromHits().

◆ src_

const edm::EDGetTokenT<reco::TrackCollection> TSGForOIDNN::src_

private

Labels for input collections.

Definition at line 50 of file TSGForOIDNN.cc.

Referenced by produce().

◆ t_estimatorH_

const edm::ESGetToken<Chi2MeasurementEstimatorBase, TrackingComponentsRecord> TSGForOIDNN::t_estimatorH_

private

Tokens for ESHandle.

Definition at line 52 of file TSGForOIDNN.cc.

Referenced by produce().

◆ t_geometryH_

const edm::ESGetToken<GlobalTrackingGeometry, GlobalTrackingGeometryRecord> TSGForOIDNN::t_geometryH_

private

Definition at line 57 of file TSGForOIDNN.cc.

Referenced by produce().

◆ t_magfieldH_

const edm::ESGetToken<MagneticField, IdealMagneticFieldRecord> TSGForOIDNN::t_magfieldH_

private

Definition at line 53 of file TSGForOIDNN.cc.

Referenced by produce().

◆ t_navSchool_

const edm::ESGetToken<NavigationSchool, NavigationSchoolRecord> TSGForOIDNN::t_navSchool_

private

Definition at line 58 of file TSGForOIDNN.cc.

Referenced by produce().

◆ t_propagatorAlongH_

const edm::ESGetToken<Propagator, TrackingComponentsRecord> TSGForOIDNN::t_propagatorAlongH_

private

Definition at line 54 of file TSGForOIDNN.cc.

Referenced by produce().

◆ t_propagatorOppositeH_

const edm::ESGetToken<Propagator, TrackingComponentsRecord> TSGForOIDNN::t_propagatorOppositeH_

private

Definition at line 55 of file TSGForOIDNN.cc.

Referenced by produce().

◆ t_SHPOpposite_

const edm::ESGetToken<Propagator, TrackingComponentsRecord> TSGForOIDNN::t_SHPOpposite_

private

Definition at line 59 of file TSGForOIDNN.cc.

Referenced by produce().

◆ t_tmpTkGeometryH_

const edm::ESGetToken<TrackerGeometry, TrackerDigiGeometryRecord> TSGForOIDNN::t_tmpTkGeometryH_

private

Definition at line 56 of file TSGForOIDNN.cc.

Referenced by produce().

◆ tf_session_

tensorflow::Session* TSGForOIDNN::tf_session_

private

Definition at line 97 of file TSGForOIDNN.cc.

Referenced by initializeTensorflow(), produce(), TSGForOIDNN(), and ~TSGForOIDNN().

◆ tf_session_HB_

tensorflow::Session* TSGForOIDNN::tf_session_HB_

private

Definition at line 104 of file TSGForOIDNN.cc.

Referenced by produce(), TSGForOIDNN(), and ~TSGForOIDNN().

◆ tf_session_HLIP_

tensorflow::Session* TSGForOIDNN::tf_session_HLIP_

private

Definition at line 106 of file TSGForOIDNN.cc.

Referenced by produce(), TSGForOIDNN(), and ~TSGForOIDNN().

◆ tf_session_HLMuS_

tensorflow::Session* TSGForOIDNN::tf_session_HLMuS_

private

Definition at line 108 of file TSGForOIDNN.cc.

Referenced by produce(), TSGForOIDNN(), and ~TSGForOIDNN().

◆ theCategory_

const std::string TSGForOIDNN::theCategory_

private

Definition at line 62 of file TSGForOIDNN.cc.

Referenced by makeSeedsWithoutHits(), and produce().

◆ updator_

const std::unique_ptr<TrajectoryStateUpdator> TSGForOIDNN::updator_

private

Definition at line 60 of file TSGForOIDNN.cc.

Referenced by makeSeedsFromHitDoublets(), and makeSeedsFromHits().

◆ useRegressor_

const bool TSGForOIDNN::useRegressor_

private

Whether to use DNN regressor (if false, will use classifier)

Definition at line 92 of file TSGForOIDNN.cc.

Referenced by initializeTensorflow(), produce(), TSGForOIDNN(), and ~TSGForOIDNN().

Classes

Public Member Functions

Static Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ TSGForOIDNN()

◆ ~TSGForOIDNN()

Member Function Documentation

◆ beginJob()

◆ evaluateClassifier()

◆ evaluateRegressor()

◆ fillDescriptions()

◆ initializeTensorflow()

◆ makeSeedsFromHitDoublets()

◆ makeSeedsFromHits()

◆ makeSeedsWithoutHits()

◆ produce()

◆ updateFeatureMap()

Member Data Documentation

◆ dnnMetadataPath_

◆ dnnModelPath_

◆ dnnModelPath_HB_

◆ dnnModelPath_HLIP_

◆ dnnModelPath_HLMuS_

◆ estimatorName_

◆ fixedErrorRescalingForHitless_

◆ getStrategyFromDNN_

◆ graphDef_

◆ graphDef_HB_

◆ graphDef_HLIP_

◆ graphDef_HLMuS_

◆ maxEtaForTOB_

◆ maxHitDoubletSeeds_

◆ maxHitlessSeeds_

◆ maxHitlessSeedsIP_

◆ maxHitlessSeedsMuS_

◆ maxHitSeeds_

◆ maxSeeds_

◆ measurementTrackerTag_

◆ metadata_

◆ minEtaForTEC_

◆ numOfHitsToTry_

◆ numOfLayersToTry_

◆ src_

◆ t_estimatorH_

◆ t_geometryH_

◆ t_magfieldH_

◆ t_navSchool_

◆ t_propagatorAlongH_

◆ t_propagatorOppositeH_

◆ t_SHPOpposite_

◆ t_tmpTkGeometryH_

◆ tf_session_

◆ tf_session_HB_

◆ tf_session_HLIP_

◆ tf_session_HLMuS_

◆ theCategory_

◆ updator_

◆ useRegressor_