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.