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modified for Phase2 DeepJet retraining model #44431
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cms-bot internal usage |
+code-checks Logs: https://cmssdt.cern.ch/SDT/code-checks/cms-sw-PR-44431/39505
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A new Pull Request was created by @hsinweihsia for master. It involves the following packages:
@Martin-Grunewald, @cmsbuild, @mmusich can you please review it and eventually sign? Thanks. cms-bot commands are listed here |
@@ -17,7 +17,7 @@ | |||
'input_5' | |||
), | |||
mightGet = cms.optional.untracked.vstring, | |||
model_path = cms.FileInPath('RecoBTag/Combined/data/DeepFlavourV01_PhaseII/model.onnx'), | |||
model_path = cms.FileInPath('RecoBTag/Combined/data/DDeepFlavourV02_PhaseII/DeepJet_retraining_phase2_new_inputs.onnx'), |
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Typo? DDeep
to Deep
?
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Sorry for the typo.
I just fixed it and git push
back to the repository.
+code-checks Logs: https://cmssdt.cern.ch/SDT/code-checks/cms-sw-PR-44431/39506
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Pull request #44431 was updated. @mmusich, @Martin-Grunewald, @cmsbuild can you please check and sign again. |
test parameters: |
@hsinweihsia please edit the PR description to link the study that motivated this update. |
@cmsbuild, please test |
+1 Summary: https://cmssdt.cern.ch/SDT/jenkins-artifacts/pull-request-integration/PR-7e7784/38186/summary.html Comparison SummarySummary:
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I have no reason to suspect issues with this PR (test results are technically fine), but unfortunately we don't seem to have any DQM / validation for the phase-2 b-tagging objects in the DQM matrix (see also issue #39362). @hsinweihsia is is something that BTV POG can work on to improve our monitoring capabilities ? |
This PR looks fine from the hlt-upgrade pov. |
+hlt |
This pull request is fully signed and it will be integrated in one of the next master IBs (tests are also fine). This pull request will now be reviewed by the release team before it's merged. @sextonkennedy, @antoniovilela, @rappoccio (and backports should be raised in the release meeting by the corresponding L2) |
+1 |
@hsinweihsia @rovere @SohamBhattacharya
do you still foresee this to happen? |
type btv |
Re-ping @hsinweihsia @rovere @SohamBhattacharya |
PR description:
The BTV@HLT group has a Phase2 DeepJet retrained model.
The target for this retraining is to retrain DeepJet and recreate/Improve TDR performance.
The retraining online performance is compared to the TDR/offline model. Please see the details here and here.
This PR is associated with the Phase2 DeepJet retraining model integration PR.
PR validation:
The model was tested locally in
CMSSW_13_1_0
.Follow the Phase 2 HLT simplified menu and
edmConfigDump
to get the configuration file and the HLT dumpphase2_hlt.py
, and inprocess.hltPfDeepFlavourJetTagsModEta2p4
andprocess.hltPfDeepFlavourJetTags, change the
model_pathto retained model
.After running
cmsRun phase2_hlt.py
, the same warnings fromInclusiveCandidateVertexFinder
andEcalRecHitProducer
are observed as running withRecoBTag/Combined/data/DeepFlavourV01_PhaseII/model.onnx
, which is the default model.Please see the details in the presentation.
If this PR is a backport please specify the original PR and why you need to backport that PR. If this PR will be backported please specify to which release cycle the backport is meant for:
It'll have to be backported to CMSSW_14_0_X.
Before submitting your pull requests, make sure you followed this checklist: