Learning WFAs with Transformers

This repo contains the code necessary to reproduce the experiments from the paper "Learning WFAs with Transformers".

Getting Started

Dependencies

This project uses Python 3.8. You can find a installer for Python 3.8 here. For Mac you can also type brew install python@3.8 into your terminal

Installing

It is recommended to run this code in a virtual environment. I used venv for this project. To setup the virtual environment and download all the necessary packages, follow the steps below

First, load the Python module you want to use:

module load python/3.8

Or use python3.8 instead in the following commands. Then, create a virtual environment in your home directory:

python -m venv $HOME/<env>

Where <env> is the name of your environment. Finally, activate the environment:

source $HOME/<env>/bin/activate

Now to install the packages simply run

pip install -r requirements.txt

Executing program

To run any training script, simply launch using the python command or using the editor/IDE of your choice. For example to run the train_counting.py experiment:

python train_counting.py

Authors

Michael Rizvi-Martel (correspondence to michael.rizvi-martel@mila.quebec) Maude Lizaire Clara Lacroce Guillaume Rabusseau

License

This project is licensed under the MIT License - see the LICENSE.md file for details