Run one of the preprocessing scripts to create graph datasets (one graph per event). For example:
python3 t3_processing.py --input ./CMSSW_15_1_0_pre2/src/RecoTracker/LSTCore/standalone/output_pu200_* --output pu200_t3/ -n 4
Each script will produce training and validation graph datasets (one file per event) in the script's configured output location.
Train either locally or on the NRP cluster. Locally you can run the project's training entrypoint (see src/main.py). To run on NRP, use the deployment YAMLs under misc/nrp/.
python3 main.py --config config.yaml
See config_pu200.yaml for example.
After training, run the analysis tools to evaluate or plot results:
python3 analysis/main.py --config config_pu200.yaml --output output/lightning_logs/version_6/ --n-events 1000 --epsilon 0.05
The plots are stored in the same lightning_logs dir as the trained model checkpoints.