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[bugfix] Improved Egamma PFID model selection consistency #38356

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merged 1 commit into from Jun 15, 2022
Merged

[bugfix] Improved Egamma PFID model selection consistency #38356

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8 changes: 5 additions & 3 deletions RecoEgamma/EgammaElectronProducers/plugins/GsfElectronProducer.cc
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Expand Up @@ -56,17 +56,19 @@ namespace {
const auto& dnn_ele_pfid = hoc->iElectronDNNEstimator->evaluate(electrons, tfSessions);
int jele = 0;
for (auto& el : electrons) {
const auto& values = dnn_ele_pfid[jele];
const auto& [iModel, values] = dnn_ele_pfid[jele];
// get the previous values
auto& mvaOutput = mva_outputs[jele];

if (abs(el.superCluster()->eta()) <= extetaboundary) {
if (iModel <= 3) { // models 0,1,2,3 have 5 outputs in this version
assert(values.size() == 5);
mvaOutput.dnn_e_sigIsolated = values[0];
mvaOutput.dnn_e_sigNonIsolated = values[1];
mvaOutput.dnn_e_bkgNonIsolated = values[2];
mvaOutput.dnn_e_bkgTau = values[3];
mvaOutput.dnn_e_bkgPhoton = values[4];
} else {
} else if (iModel == 4) { //etaExtended model has 3 outputs
assert(values.size() == 3);
mvaOutput.dnn_e_sigIsolated = values[0];
mvaOutput.dnn_e_sigNonIsolated = 0.0;
mvaOutput.dnn_e_bkgNonIsolated = values[1];
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4 changes: 2 additions & 2 deletions RecoEgamma/EgammaElectronProducers/python/gedGsfElectrons_cfi.py
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Expand Up @@ -36,8 +36,8 @@
"RecoEgamma/ElectronIdentification/data/Ele_PFID_dnn/Run3Summer21_120X/EE_highpT/endcap_highpT_scaler.txt",
"RecoEgamma/ElectronIdentification/data/Ele_PFID_dnn/Run3Winter22_122X/exteta1/scaler.txt",
"RecoEgamma/ElectronIdentification/data/Ele_PFID_dnn/Run3Winter22_122X/exteta2/scaler.txt"

]
],
outputDim = [5,5,5,5,3]
)
)

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3 changes: 2 additions & 1 deletion RecoEgamma/EgammaPhotonProducers/src/GEDPhotonProducer.cc
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Expand Up @@ -1030,8 +1030,9 @@ void GEDPhotonProducer::fillPhotonCollection(edm::Event& evt,
const auto& dnn_photon_pfid = globalCache()->photonDNNEstimator->evaluate(outputPhotonCollection, tfSessions_);
size_t ipho = 0;
for (auto& photon : outputPhotonCollection) {
const auto& values = dnn_photon_pfid[ipho];
const auto& [iModel, values] = dnn_photon_pfid[ipho];
reco::Photon::PflowIDVariables pfID;
// The model index it is not useful for the moment
pfID.dnn = values[0];
photon.setPflowIDVariables(pfID);
ipho++;
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5 changes: 3 additions & 2 deletions RecoEgamma/EgammaTools/interface/EgammaDNNHelper.h
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Expand Up @@ -49,8 +49,9 @@ namespace egammaTools {
// which has access to all the variables.
std::pair<uint, std::vector<float>> getScaledInputs(const std::map<std::string, float>& variables) const;

std::vector<std::vector<float>> evaluate(const std::vector<std::map<std::string, float>>& candidates,
const std::vector<tensorflow::Session*>& sessions) const;
std::vector<std::pair<uint, std::vector<float>>> evaluate(
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not for this PR, but I think the same comment applies here as was suggested at the DeepSC PR:
these kind of supernested structures are easy to write down but hard to reason about later. It would be better to define classes that encapsulate the required data.

const std::vector<std::map<std::string, float>>& candidates,
const std::vector<tensorflow::Session*>& sessions) const;

private:
void initTensorFlowGraphs();
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19 changes: 10 additions & 9 deletions RecoEgamma/EgammaTools/src/EgammaDNNHelper.cc
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Expand Up @@ -97,8 +97,9 @@ std::pair<uint, std::vector<float>> EgammaDNNHelper::getScaledInputs(
return std::make_pair(modelIndex, inputs);
}

std::vector<std::vector<float>> EgammaDNNHelper::evaluate(const std::vector<std::map<std::string, float>>& candidates,
const std::vector<tensorflow::Session*>& sessions) const {
std::vector<std::pair<uint, std::vector<float>>> EgammaDNNHelper::evaluate(
const std::vector<std::map<std::string, float>>& candidates,
const std::vector<tensorflow::Session*>& sessions) const {
/*
Evaluate the PFID DNN for all the electrons/photons.
nModels_ are defined depending on modelIndex --> we need to build N input tensors to evaluate
Expand All @@ -109,17 +110,17 @@ std::vector<std::vector<float>> EgammaDNNHelper::evaluate(const std::vector<std:
2) Prepare the input tensors for the models
3) Run the models and get the output for each candidate
4) Sort the output by candidate index
5) Return the DNN outputs
5) Return the DNN outputs along with the model index used on it

*/
size_t nCandidates = candidates.size();
std::vector<std::vector<int>> indexMap(nModels_); // for each model; the list of candidate index is saved
std::vector<std::vector<uint>> indexMap(nModels_); // for each model; the list of candidate index is saved
std::vector<std::vector<float>> inputsVectors(nCandidates);
std::vector<uint> counts(nModels_);

LogDebug("EgammaDNNHelper") << "Working on " << nCandidates << " candidates";

int icand = 0;
uint icand = 0;
for (auto& candidate : candidates) {
LogDebug("EgammaDNNHelper") << "Working on candidate: " << icand;
const auto& [model_index, inputs] = getScaledInputs(candidate);
Expand Down Expand Up @@ -152,8 +153,8 @@ std::vector<std::vector<float>> EgammaDNNHelper::evaluate(const std::vector<std:
}

// Define the output and run
// Define the output and run
std::vector<std::pair<int, std::vector<float>>> outputs;
// The initial output is [(cand_index,(model_index, outputs)),.. ]
std::vector<std::pair<uint, std::pair<uint, std::vector<float>>>> outputs;
// Run all the models
for (size_t m = 0; m < nModels_; m++) {
if (counts[m] == 0)
Expand All @@ -174,12 +175,12 @@ std::vector<std::vector<float>> EgammaDNNHelper::evaluate(const std::vector<std:
}
// Get the original index of the electorn in the original order
const auto cand_index = indexMap[m][b];
outputs.push_back(std::make_pair(cand_index, result));
outputs.push_back(std::make_pair(cand_index, std::make_pair(m, result)));
}
}
// Now we have just to re-order the outputs
std::sort(outputs.begin(), outputs.end());
std::vector<std::vector<float>> final_outputs(outputs.size());
std::vector<std::pair<uint, std::vector<float>>> final_outputs(outputs.size());
std::transform(outputs.begin(), outputs.end(), final_outputs.begin(), [](auto a) { return a.second; });

return final_outputs;
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4 changes: 2 additions & 2 deletions RecoEgamma/ElectronIdentification/interface/ElectronDNNEstimator.h
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Expand Up @@ -20,8 +20,8 @@ class ElectronDNNEstimator {
std::map<std::string, float> getInputsVars(const reco::GsfElectron& ele) const;

// Evaluate the DNN on all the electrons with the correct model
std::vector<std::vector<float>> evaluate(const reco::GsfElectronCollection& ele,
const std::vector<tensorflow::Session*>& sessions) const;
std::vector<std::pair<uint, std::vector<float>>> evaluate(const reco::GsfElectronCollection& ele,
const std::vector<tensorflow::Session*>& sessions) const;

// List of input variables names used to check the variables request as
// inputs in a dynamic way from configuration file.
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4 changes: 2 additions & 2 deletions RecoEgamma/ElectronIdentification/src/ElectronDNNEstimator.cc
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Expand Up @@ -15,7 +15,7 @@ inline uint electronModelSelector(
Selection of the model to be applied on the electron based on pt/eta cuts or whatever selection
*/
const auto pt = vars.at("pt");
const auto absEta = std::abs(vars.at("eta"));
const auto absEta = std::abs(vars.at("superCluster.eta"));
if (absEta <= endcapBoundary) {
if (pt < ptThr)
return 0;
Expand Down Expand Up @@ -156,7 +156,7 @@ std::map<std::string, float> ElectronDNNEstimator::getInputsVars(const reco::Gsf
return variables;
}

std::vector<std::vector<float>> ElectronDNNEstimator::evaluate(
std::vector<std::pair<uint, std::vector<float>>> ElectronDNNEstimator::evaluate(
const reco::GsfElectronCollection& electrons, const std::vector<tensorflow::Session*>& sessions) const {
// Collect the map of variables for each candidate and call the dnnHelper
// Scaling, model selection and running is performed in the helper
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4 changes: 2 additions & 2 deletions RecoEgamma/PhotonIdentification/interface/PhotonDNNEstimator.h
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Expand Up @@ -21,8 +21,8 @@ class PhotonDNNEstimator {
std::map<std::string, float> getInputsVars(const reco::Photon& ele) const;

// Evaluate the DNN on all the electrons with the correct model
std::vector<std::vector<float>> evaluate(const reco::PhotonCollection& ele,
const std::vector<tensorflow::Session*>& sessions) const;
std::vector<std::pair<uint, std::vector<float>>> evaluate(const reco::PhotonCollection& ele,
const std::vector<tensorflow::Session*>& sessions) const;

// List of input variables names used to check the variables request as
// inputs in a dynamic way from configuration file.
Expand Down
4 changes: 2 additions & 2 deletions RecoEgamma/PhotonIdentification/src/PhotonDNNEstimator.cc
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Expand Up @@ -66,8 +66,8 @@ std::map<std::string, float> PhotonDNNEstimator::getInputsVars(const reco::Photo
return variables;
}

std::vector<std::vector<float>> PhotonDNNEstimator::evaluate(const reco::PhotonCollection& photons,
const std::vector<tensorflow::Session*>& sessions) const {
std::vector<std::pair<uint, std::vector<float>>> PhotonDNNEstimator::evaluate(
const reco::PhotonCollection& photons, const std::vector<tensorflow::Session*>& sessions) const {
// Collect the map of variables for each candidate and call the dnnHelper
// Scaling, model selection and running is performed in the helper
std::vector<std::map<std::string, float>> inputs;
Expand Down