Modeling Relational Data with Graph Convolutional Networks in PaddlePaddle
This is a PaddlePaddle implementation of the Relational Graph Convolutional Networks (R-GCN) described in the paper:
Schlichtkrull, Michael, et al. "Modeling relational data with graph convolutional networks." European semantic web conference. Springer, Cham, 2018.
The code in this repo is based on or refers to https://github.com/berlincho/RGCN-pytorch and https://github.com/tkipf/relational-gcn
- Hardware：CPU (RAM larger than 36G is recommended)
- python-3.8.12
- paddlepaddle-2.1.3
- paddlenlp-2.1.1
- rdflib-6.0.2
- wget-3.2
- h5py-3.5.0
- install requirements via pip install -r requirements.txt
train: python run.py --train
test: python run.py