This is our PyTorch implementation code for our paper:
[1] Xu Yuhao, Wang Zhenhai, Wang ZhiRu, Guo YunLong, Fan Rong, Tian Hongyu and Wang Xing . “SimDCL: dropout-based simple graph contrastive learning for recommendation.” Complex & Intelligent Systems (2023)
recbole==1.1.1
pyg>=2.0.4
pytorch>=1.7.0
python>=3.7.0
With the source code, you can use the provided script for initial usage of our library:
python run_recbole_gnn.py
If you want to change the models or datasets, just run the script by setting additional command parameters:
python run_recbole_gnn.py -m [model] -d [dataset]