Configuration Layout#

Start here: experiment configs#

Each YAML file in ``conf/`` is a self-contained experiment config. Run training or inference by selecting one:

python train.py --config-name=bumper_geotransolver_oneshot
python train.py --config-name=crash_geotransolver_oneshot
python inference.py --config-name=crash_geotransolver_oneshot

To add a new experiment, copy an existing file in conf/ and edit data paths, model, and features.


Component configs (advanced)#

The subfolders (model/, datapipe/, reader/, training/, inference/) contain configs referenced by experiments. You rarely need to edit them unless customizing models, readers, or training defaults.

Path

Purpose

model/

Model architectures (selected via experiment)

datapipe/

Dataset and feature configs

reader/

Data format readers (VTP, Zarr)

training/

Training hyperparameters

inference/

Inference options