Fast experiments for NLP and ML. See docs here.
I built this library to prototype ideas quickly. In essence it combines Hydra and Pytorch Lightning for supervised learning. The following are supported with command line or config tweaks (e.g. no additional boilerplate code):
- checkpointing
- early stopping
- auto git diffs
- logging to wandb
- Slurm launcher
pip install -e . # add [dev] if you want to run tests and build docs.
# for latest
pip install git+https://github.com/r2llab/wrangl
# pypi release
pip install wranglSee the documentation for how to use Wrangl.
Examples of projects using Wrangl are found in wrangl.examples.
In particular wrangl.examples.learn.xor_clf shows an example of using Wrangl to quickly set up a supervised classification task.