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Update to DNN-based strategy for outside-in seed generation in Muon HLT #37437
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+code-checks Logs: https://cmssdt.cern.ch/SDT/code-checks/cms-sw-PR-37437/29132
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A new Pull Request was created by @kondratyevd (Dmitry Kondratyev) for master. It involves the following packages:
@jpata, @cmsbuild, @clacaputo, @slava77 can you please review it and eventually sign? Thanks. cms-bot commands are listed here |
@missirol This together with the cms-data PR is for the HLT and would ideally also be backported to 12_3_0 if time permits. |
Thanks for the info, @JanFSchulte . It looks like this PR is only updating the producer, so it does not really need to be tested together with cms-data/RecoMuon-TrackerSeedGenerator#4 , correct? Concerning the backport to |
urgent MUO-HLT developers intend to have this update backported in time for ("urgent" here means "to be backported in time for |
Yes, the cms-data PR does not affect the tests. In fact, the producer is not run in any tests at all, so they are meaningless for this PR. |
assign hlt |
New categories assigned: hlt @missirol,@Martin-Grunewald you have been requested to review this Pull request/Issue and eventually sign? Thanks |
please test |
The model file is fairly large (the largest I'm aware of in CMSSW): BIN +10.1 MB OIseeding/DNNclassifier_Run3_inclusive.pb Have you rechecked memory and CPU performance of the model? I suppose it's for HLT to evaluate if it's appropriate (since AFAIK this doesn't run offline), but just to be aware. |
Thanks for pointing this out (for the record, this does not run at HLT either yet, not even the previous version of this DNN did). @JanFSchulte @khaosmos93 @kondratyevd , for CPU timing I see the slides have the numbers for HLT, but do you also have numbers for the amount of memory used by the model? ( cc: @silviodonato ) |
+1 Summary: https://cmssdt.cern.ch/SDT/jenkins-artifacts/pull-request-integration/PR-553822/23636/summary.html Comparison SummarySummary:
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+hlt
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+reconstruction
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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. @perrotta, @dpiparo, @qliphy (and backports should be raised in the release meeting by the corresponding L2) |
@JanFSchulte @khaosmos93 @kondratyevd , please address this point, and open a backport of this PR to |
I have generated the igprof memory reports, but I didn't manage to turn them into interpretable web-navigable reports. The sql3 files are here (lxplus): |
I uploaded your memory profiles here:
Since this is probably a HLT workflow, I'm not really able to tell much about the expected/observed use from these. |
@jpata ah, I used the default igprof instructions and forgot to take into account Slava's recommendations to the previous PR: #35237 (comment). |
@jpata the new reports are available at |
Looking at the logs, it seems that unfortunately in the most recent tests the input file failed to open. |
+1
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PR description:
This is a follow-up on #35237.
The DNN-based approach to outside-in seed generation for muon HLT has been revised.
TSGForOIDNN.cc
plugin: remove split into barrel and endcap; use one model for all muons.The updated model is added to
cms-data
: cms-data/RecoMuon-TrackerSeedGenerator#4. The older classifier models will not work with the updated plugin.PR validation:
Slides describing the update: link.
The performance was checked on J/psi (low-pT) and Drell-Yan (high-pT) datasets. Overall HLT efficiency is similar for all models, while the timing for the newly trained models is improved.