Please refer to https://github.com/snap-stanford/pretrain-gnns#installation for environment setup and https://github.com/snap-stanford/pretrain-gnns#dataset-download to download dataset.

If you cannot manage to install the old torch-geometric version, one alternative way is to use the new one (maybe ==1.6.0) and make some modifications based on this issue snap-stanford/pretrain-gnns#14. This might leads to some inconsistent results with those in the paper.

To reproduce the transfer learning results in our paper, simply run finetune.sh.

We release our pre-trained model in folder models_graphtrans.

We also give our fine-tune log: srgcl_finetune_log.log from which we got the results in our paper.

We suggest to run it on Linux Platform.

python pretrain_sr_gcl.py

The backbone implementation is reference to https://github.com/snap-stanford/pretrain-gnns and https://github.com/Shen-Lab/GraphCL.