Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"

Related tags

Deep Learning Subg-Con
Overview

Subg-Con

Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning (Jiao et al., ICDM 2020): https://arxiv.org/abs/2009.10273

Overview

Here we provide an implementation of Subg-Con in PyTorch and the geometric deep learning extension library, Pytorch Geometric. The repository is organised as follows:

  • subgcon.py is the implementation of the Subg-Con pipeline;
  • subgraph.py is the implementation of subgraph extractor;
  • model.py is the implementation of components for Subg-Con, including a GNN layer, a pooling layer, and a scoring function;
  • utils_mp.py is the necessary processing subroutines;
  • dataset/ will contain the automatically downloaded datasets;
  • subgraph/ will contain the processed subgraphs.

Finally, train.py puts all of the above together and may be used to execute a full training. The codes can be run on six datasets, including Cora, CiteSeer, PubMed, PPI, Flickr, and Reddit.

Train SubgCon

python train.py --dataset DATASET_NAME

Train SubgCon+

python train+.py --dataset DATASET_NAME

Dependencies

Reference

If you make advantage of Subg-Con in your research, please cite the following in your manuscript:

@article{jiao2020sub,
  title={Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning},
  author={Jiao, Yizhu and Xiong, Yun and Zhang, Jiawei and Zhang, Yao and Zhang, Tianqi and Zhu, Yangyong},
  journal={arXiv preprint arXiv:2009.10273},
  year={2020}
}
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Comments
  • Code error

    Code error

    Subg-Con-master\utils_mp.py", line 77 list(pool.imap_unordered(self.process(path), list(range(node_num)), chunksize=1000)) TypeError: process() missing 1 required positional argument: 'seed'

    opened by wangzeyu135798 1
  • Can not reproduce the results in the parer!

    Can not reproduce the results in the parer!

    Hi! I clone your code and run the command, but the acc of Cora is only 0.716. Is there anything wrong with the config of your code? My environment is Pytorch1.6, Pytorch Geometric 1.7. Hoping for you answer, thanks.

    opened by yifanQi98 1
  • the codes have bugs while dealing with PPI dataset

    the codes have bugs while dealing with PPI dataset

    PPI dataset has 24 graphs, but the codes in line 50 only use one graph. And these graphs do not contain (train/valid/test) masks, so line 52 will report a bug/. I hope you will remedy these problems. Thanks for contributing these fabulous codes.

    opened by ZhuYun97 3
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