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Low-Q2 particle reconstruction using onnx framework #1697

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merged 20 commits into from
Jan 19, 2025
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simonge
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@simonge simonge commented Jan 7, 2025

Briefly, what does this PR introduce?

Adds ML workflow for the Low-Q2 Tagger particle reconstruction based on the onnx framework provided. As an alternative to the TMVA description.

Currently not added by default as there are a number of things which need to be adapted. I will follow up with a note of the relevant issues/PRs.

What kind of change does this PR introduce?

  • Bug fix (issue #__)
  • New feature (issue #__)
  • Documentation update
  • Other: __

Please check if this PR fulfills the following:

  • Tests for the changes have been added
  • Documentation has been added / updated
  • Changes have been communicated to collaborators

Does this PR introduce breaking changes? What changes might users need to make to their code?

No

Does this PR change default behavior?

No

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simonge commented Jan 8, 2025

Essential for running the inference:

Automated training workflow

Desired to allow the Particles output from the inference to better be injected into ReconstructedParticles.

Needed for producing minimal files which can test replacement onnx files

@simonge simonge requested a review from veprbl January 8, 2025 14:59
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Looks great

@simonge simonge added this pull request to the merge queue Jan 19, 2025
Merged via the queue into main with commit 61b9b07 Jan 19, 2025
85 of 86 checks passed
@simonge simonge deleted the Output_Low-Q2_Tensor branch January 19, 2025 18:16
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2 participants