Implementation of paper "Graph Condensation for Graph Neural Networks"

Wei Jin

Last update: Dec 4, 2022

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Deep Learning GCond

Overview

GCond

A PyTorch implementation of paper "Graph Condensation for Graph Neural Networks"

Code will be released soon. Stay tuned :)

Abstract

We propose and study the problem of graph condensation for graph neural networks (GNNs). Specifically, we aim to condense the large, original graph into a small, synthetic and highly-informative graph, such that GNNs trained on the small graph and large graph have comparable performance. Extensive experiments have demonstrated the effectiveness of the proposed framework in condensing different graph datasets into informative smaller graphs. In particular, we are able to approximate the original test accuracy by 95.3% on Reddit, 99.8% on Flickr and 99.0% on Citeseer, while reducing their graph size by more than 99.9%, and the condensed graphs can be used to train various GNN architectures.

Cite

For more information, you can take a look at the paper.

If you find this repo to be useful, please cite our paper. Thank you.

@misc{jin2021graph,
      title={Graph Condensation for Graph Neural Networks}, 
      author={Wei Jin and Lingxiao Zhao and Shichang Zhang and Yozen Liu and Jiliang Tang and Neil Shah},
      year={2021},
      eprint={2110.07580},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

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Comments

Runtime error:expect scalar type Long but found Int

I've been trying reproducing the performance of your paper and this runtime error keeps popping up.After a brief look,I think Line 183 in utils.py should turn "batch" into a LongTensor type.I managed to fix this problem and reproduced the performance.I wonder if you could check if I'm right so that I can move on to other issues.

opened by HunterLep 4
missing file train_cond_tranduct_sampler.py

In scripts/run_main.sh, there is a line: python train_cond_tranduct_sampler.py --dataset ogbn-arxiv --mlp=0 --nlayers=2 --sgc=1 --lr_feat=0.01 --gpu_id=3 --lr_adj=0.01 --r=${r} --seed=1 --inner=3 --epochs=1000 --save=0

But it seems like the python file train_cond_tranduct_sampler.py is not in this repository. I've tried to use train_gcond_transduct.py instead, but the argument 'mlp' is not in it.

Could you provide this file or some information on the argument 'mlp'? It would really help me out. :)

opened by agoyang 2
The exp result reproduce of the whole dataset on Table 2

Hi, I wonder how to produce the whole dataset's experiment results shown in Table 2. Does it directly run the whole graph (like Cora) on a model (if yes, does it run on GCN?), without any reduction rate? or set the reduction rate as 1?

opened by gegemy 0
questions of the coarsen part

could you provide the coarsen part's source code? the coarsen operates on the whole graph, but your work implements the inductive train graph for the label part? could you please give more details about this part?

opened by Amanda-Zheng 3

Implementation of paper "Graph Condensation for Graph Neural Networks"

Related tags

Overview

GCond

Abstract

Cite

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Comments

Runtime error:expect scalar type Long but found Int

missing file train_cond_tranduct_sampler.py

The exp result reproduce of the whole dataset on Table 2

questions of the coarsen part

Owner

Wei Jin

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