The repository implements the Transformer over Directed Acyclic Graph (DAG transformer) in Pytorch Geometric.
Tested with Python 3.7, PyTorch 1.13.1, and PyTorch Geometric 2.3.1.
The dependencies are managed by [conda]:
pip install -r requirements.txt
./NA
Experiment code over the NA
dataset.
./ogbg-code2
Experiment code over the ogbg-code2
data from OGB.
./self-citation
Experiment code over the self-citation
dataset.
./Node_classification_citation
Experiment code over the Cora, Citeseer, Pubmed
datasets.
If you find our codes useful, please consider citing our work
@inproceedings{
luo2023transformers,
title={Transformers over Directed Acyclic Graphs},
author={Yuankai Luo and Veronika Thost and Lei Shi},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
year={2023},
url={https://openreview.net/forum?id=g49s1N5nmO}
}