GRACE-pytorch

This repo is an unofficial implementation of Graph Clustering with Embedding Propagation in Python 3 and PyTorch. See the original code in Python 2 and TensorFlow. Note that I do not guarantee the correctness of this code.

TO-DO

• add GRACE model
• fix bugs: the gradient of self.mean is not being properly updated
• fix other bugs...

Only test on...

• Python 3.11
• SciPy 1.11.3
• Numpy 1.26.0
• tqdm 4.66.1
• scikit-learn 1.3.1
• PyTorch 2.1.0

Note: I don't think this code is version-sensitive, so maybe you don't need to be fully compliant with these.

Train GRACE

Try this script to train the model on cora dataset.

python train.py --device cuda --dataset cora --embed_dim 512 --encoder_hidden 512 --decoder_hidden 512 --learning_rate 5e-5 --pre_epoch 1000 --epoch 2000

Acknowledgments

This work partly uses the code from the original version.

Cite

If you find this work useful, please cite the original paper.

@INPROCEEDINGS{9378031,
  author={Yang, Carl and Liu, Liyuan and Liu, Mengxiong and Wang, Zongyi and Zhang, Chao and Han, Jiawei},
  booktitle={2020 IEEE International Conference on Big Data (Big Data)}, 
  title={Graph Clustering with Embedding Propagation}, 
  year={2020},
  volume={},
  number={},
  pages={858-867},
  doi={10.1109/BigData50022.2020.9378031}}