# clone repository and call this from dnn_reco directory:
pip install -e ./ --process-dependency-links

# Create data transformation model:
# We must first create a transformation model that will take care of data normalization and transformation
python create_trafo_model.py /PATH/TO/MY/YAML/CONFIG/FILE

# Train model:
# This step can be run with as many config files and settings as you wish.
# The settings and number of training iterations is automatically logged and will be exported together
# with the final model.
python train_model.py /PATH/TO/MY/YAML/CONFIG/FILE

# Export model:
# Once the model is trained, we can export it, so that it can be used to reconstruct IceCube events with the provided I3Module
python export_model.py /PATH/TO/MY/YAML/CONFIG/FILE -s /PATH/TO/CONFIG/FILE/USED/TO/CREATE/TRAINING/DATA -o OUTPUT/Directory

# More documentation can be found here: https://icecube.wisc.edu/~mhuennefeld/docs/dnn_reco/html/