MLPFProducer Class Reference

Inheritance diagram for MLPFProducer:

Public Member Functions
	MLPFProducer (const edm::ParameterSet &, const ONNXRuntime *)
void	produce (edm::Event &event, const edm::EventSetup &setup) override
Public Member Functions inherited from edm::stream::EDProducer< edm::GlobalCache< ONNXRuntime > >
	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
const EDProducer &	operator= (const EDProducer &)=delete

Static Public Member Functions
static void	fillDescriptions (edm::ConfigurationDescriptions &descriptions)
static void	globalEndJob (const ONNXRuntime *)
static std::unique_ptr< ONNXRuntime >	initializeGlobalCache (const edm::ParameterSet &)

Private Attributes
const edm::EDGetTokenT< reco::PFBlockCollection >	inputTagBlocks_
const edm::EDPutTokenT< reco::PFCandidateCollection >	pfCandidatesPutToken_

Additional Inherited Members
Public Types inherited from edm::stream::EDProducer< edm::GlobalCache< ONNXRuntime > >
using	CacheTypes = CacheContexts< T... >
using	GlobalCache = typename CacheTypes::GlobalCache
using	HasAbility = AbilityChecker< T... >
using	InputProcessBlockCache = typename CacheTypes::InputProcessBlockCache
using	LuminosityBlockCache = typename CacheTypes::LuminosityBlockCache
using	LuminosityBlockContext = LuminosityBlockContextT< LuminosityBlockCache, RunCache, GlobalCache >
using	LuminosityBlockSummaryCache = typename CacheTypes::LuminosityBlockSummaryCache
using	RunCache = typename CacheTypes::RunCache
using	RunContext = RunContextT< RunCache, GlobalCache >
using	RunSummaryCache = typename CacheTypes::RunSummaryCache

Detailed Description

Definition at line 17 of file MLPFProducer.cc.

Constructor & Destructor Documentation

MLPFProducer()

MLPFProducer::MLPFProducer ( const edm::ParameterSet &  cfg, const ONNXRuntime *  cache  )

explicit

Definition at line 33 of file MLPFProducer.cc.

    : pfCandidatesPutToken_{produces<reco::PFCandidateCollection>()},
      inputTagBlocks_(consumes<reco::PFBlockCollection>(cfg.getParameter<edm::InputTag>("src"))) {}

Member Function Documentation

fillDescriptions()

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

static

Definition at line 168 of file MLPFProducer.cc.

References edm::ConfigurationDescriptions::addWithDefaultLabel(), submitPVResolutionJobs::desc, and HLT_2022v14_cff::InputTag.

                                                                              {
  edm::ParameterSetDescription desc;
  desc.add<edm::InputTag>("src", edm::InputTag("particleFlowBlock"));
  desc.add<edm::FileInPath>(
      "model_path",
      edm::FileInPath(
          "RecoParticleFlow/PFProducer/data/mlpf/"
          "mlpf_2021_11_16__no_einsum__all_data_cms-best-of-asha-scikit_20211026_042043_178263.workergpu010.onnx"));
  descriptions.addWithDefaultLabel(desc);
}

globalEndJob()

void MLPFProducer::globalEndJob ( const ONNXRuntime *  cache )

static

Definition at line 166 of file MLPFProducer.cc.

{}

initializeGlobalCache()

std::unique_ptr< ONNXRuntime > MLPFProducer::initializeGlobalCache ( const edm::ParameterSet &  params )

static

Definition at line 162 of file MLPFProducer.cc.

References contentValuesFiles::fullPath, and submitPVValidationJobs::params.

                                                                                            {
  return std::make_unique<ONNXRuntime>(params.getParameter<edm::FileInPath>("model_path").fullPath());
}

produce()

void MLPFProducer::produce ( edm::Event &  event, const edm::EventSetup &  setup  )

override

Definition at line 37 of file MLPFProducer.cc.

References reco::mlpf::argMax(), cms::cuda::assert(), gather_cfg::blocks, gather_cfg::cout, reco::mlpf::getElementProperties(), reco::mlpf::getPFElements(), reco::mlpf::IDX_CHARGE, reco::mlpf::IDX_CLASS, reco::mlpf::IDX_COS_PHI, reco::mlpf::IDX_ENERGY, reco::mlpf::IDX_ETA, reco::mlpf::IDX_PT, reco::mlpf::IDX_SIN_PHI, PixelMapPlotter::inputs, inputTagBlocks_, CommonMethods::isnan(), reco::mlpf::LSH_BIN_SIZE, reco::mlpf::makeCandidate(), SiStripPI::max, reco::mlpf::normalize(), reco::mlpf::NUM_ELEMENT_FEATURES, reco::mlpf::NUM_MAX_ELEMENTS_BATCH, reco::mlpf::NUM_OUTPUT_FEATURES, convertSQLitetoXML_cfg::output, PatBasicFWLiteJetAnalyzer_Selector_cfg::outputs, reco::mlpf::pdgid_encoding, pfCandidatesPutToken_, reco::PFBlockElement::PS1, reco::PFBlockElement::PS2, reco::mlpf::setCandidateRefs(), reco::PFBlockElement::TRACK, and reco::PFBlockElement::type().

                                                                      {
  using namespace reco::mlpf;

  const auto& blocks = event.get(inputTagBlocks_);
  const auto& all_elements = getPFElements(blocks);

  std::vector<const reco::PFBlockElement*> selected_elements;
  unsigned int num_elements_total = 0;
  for (const auto* pelem : all_elements) {
    if (pelem->type() == reco::PFBlockElement::PS1 || pelem->type() == reco::PFBlockElement::PS2) {
      continue;
    }
    num_elements_total += 1;
    selected_elements.push_back(pelem);
  }
  const auto tensor_size = LSH_BIN_SIZE * std::max(2u, (num_elements_total / LSH_BIN_SIZE + 1));

#ifdef MLPF_DEBUG
  assert(num_elements_total < NUM_MAX_ELEMENTS_BATCH);
  //tensor size must be a multiple of the bin size and larger than the number of elements
  assert(tensor_size <= NUM_MAX_ELEMENTS_BATCH);
  assert(tensor_size % LSH_BIN_SIZE == 0);
#endif

#ifdef MLPF_DEBUG
  std::cout << "tensor_size=" << tensor_size << std::endl;
#endif

  //Fill the input tensor (batch, elems, features) = (1, tensor_size, NUM_ELEMENT_FEATURES)
  std::vector<std::vector<float>> inputs(1, std::vector<float>(NUM_ELEMENT_FEATURES * tensor_size, 0.0));
  unsigned int ielem = 0;
  for (const auto* pelem : selected_elements) {
    if (ielem > tensor_size) {
      continue;
    }

    const auto& elem = *pelem;

    //prepare the input array from the PFElement
    const auto& props = getElementProperties(elem);

    //copy features to the input array
    for (unsigned int iprop = 0; iprop < NUM_ELEMENT_FEATURES; iprop++) {
      inputs[0][ielem * NUM_ELEMENT_FEATURES + iprop] = normalize(props[iprop]);
    }
    ielem += 1;
  }

  //run the GNN inference, given the inputs and the output.
  const auto& outputs = globalCache()->run({"x:0"}, inputs, {{1, tensor_size, NUM_ELEMENT_FEATURES}});
  const auto& output = outputs[0];
#ifdef MLPF_DEBUG
  assert(output.size() == tensor_size * NUM_OUTPUT_FEATURES);
#endif

  std::vector<reco::PFCandidate> pOutputCandidateCollection;
  for (size_t ielem = 0; ielem < num_elements_total; ielem++) {
    std::vector<float> pred_id_probas(IDX_CLASS + 1, 0.0);
    const reco::PFBlockElement* elem = selected_elements[ielem];

    for (unsigned int idx_id = 0; idx_id <= IDX_CLASS; idx_id++) {
      auto pred_proba = output[ielem * NUM_OUTPUT_FEATURES + idx_id];
#ifdef MLPF_DEBUG
      assert(!std::isnan(pred_proba));
#endif
      pred_id_probas[idx_id] = pred_proba;
    }

    auto imax = argMax(pred_id_probas);

    //get the most probable class PDGID
    int pred_pid = pdgid_encoding[imax];

#ifdef MLPF_DEBUG
    std::cout << "ielem=" << ielem << " inputs:";
    for (unsigned int iprop = 0; iprop < NUM_ELEMENT_FEATURES; iprop++) {
      std::cout << iprop << "=" << inputs[0][ielem * NUM_ELEMENT_FEATURES + iprop] << " ";
    }
    std::cout << std::endl;
    std::cout << "ielem=" << ielem << " pred: pid=" << pred_pid << std::endl;
#endif

    //a particle was predicted for this PFElement, otherwise it was a spectator
    if (pred_pid != 0) {
      //muons and charged hadrons should only come from tracks, otherwise we won't have track references to pass downstream
      if (((pred_pid == 13) || (pred_pid == 211)) && elem->type() != reco::PFBlockElement::TRACK) {
        pred_pid = 130;
      }

      if (elem->type() == reco::PFBlockElement::TRACK) {
        const auto* eltTrack = dynamic_cast<const reco::PFBlockElementTrack*>(elem);

        //a track with no muon ref should not produce a muon candidate, instead we interpret it as a charged hadron
        if (pred_pid == 13 && eltTrack->muonRef().isNull()) {
          pred_pid = 211;
        }

        //tracks from displaced vertices need reference debugging downstream as well, so we just treat them as neutrals for the moment
        if ((pred_pid == 211) && (eltTrack->isLinkedToDisplacedVertex())) {
          pred_pid = 130;
        }
      }

      //get the predicted momentum components
      float pred_pt = output[ielem * NUM_OUTPUT_FEATURES + IDX_PT];
      float pred_eta = output[ielem * NUM_OUTPUT_FEATURES + IDX_ETA];
      float pred_sin_phi = output[ielem * NUM_OUTPUT_FEATURES + IDX_SIN_PHI];
      float pred_cos_phi = output[ielem * NUM_OUTPUT_FEATURES + IDX_COS_PHI];
      float pred_e = output[ielem * NUM_OUTPUT_FEATURES + IDX_ENERGY];
      float pred_charge = output[ielem * NUM_OUTPUT_FEATURES + IDX_CHARGE];

      auto cand = makeCandidate(pred_pid, pred_charge, pred_pt, pred_eta, pred_sin_phi, pred_cos_phi, pred_e);
      setCandidateRefs(cand, selected_elements, ielem);
      pOutputCandidateCollection.push_back(cand);

#ifdef MLPF_DEBUG
      std::cout << "ielem=" << ielem << " cand: pid=" << cand.pdgId() << " E=" << cand.energy() << " pt=" << cand.pt()
                << " eta=" << cand.eta() << " phi=" << cand.phi() << " charge=" << cand.charge() << std::endl;
#endif
    }
  }  //loop over PFElements

  event.emplace(pfCandidatesPutToken_, pOutputCandidateCollection);
}

Member Data Documentation

inputTagBlocks_

const edm::EDGetTokenT<reco::PFBlockCollection> MLPFProducer::inputTagBlocks_

private

Definition at line 30 of file MLPFProducer.cc.

Referenced by produce().

pfCandidatesPutToken_

const edm::EDPutTokenT<reco::PFCandidateCollection> MLPFProducer::pfCandidatesPutToken_

private

Definition at line 29 of file MLPFProducer.cc.

Referenced by produce().