/examples/pytorch/rgcn

Relational-GCN

• Paper: Modeling Relational Data with Graph Convolutional Networks
• Author's code for entity classification: https://github.com/tkipf/relational-gcn
• Author's code for link prediction: https://github.com/MichSchli/RelationPrediction

Dependencies

• PyTorch 1.10
• rdflib
• pandas
• tqdm
• TorchMetrics

pip install rdflib pandas

Example code was tested with rdflib 4.2.2 and pandas 0.23.4

Entity Classification

For AIFB, MUTAG, BGS and AM,

python entity.py -d aifb --wd 0 --gpu 0
python entity.py -d mutag --n-bases 30 --gpu 0
python entity.py -d bgs --n-bases 40 --gpu 0
python entity.py -d am --n-bases 40 --n-hidden 10 --gpu 0

Entity Classification with minibatch

For AIFB, MUTAG, BGS and AM,

python entity_sample.py -d aifb --wd 0 --gpu 0 --fanout='20,20' --batch-size 128
python entity_sample.py -d mutag --n-bases 30 --gpu 0 --batch-size 64 --fanout='-1,-1' --use-self-loop --n-epochs 20 --dropout 0.5
python entity_sample.py -d bgs --n-bases 40 --gpu 0 --fanout='-1,-1'  --n-epochs=16 --batch-size=16 --dropout 0.3
python entity_sample.py -d am --n-bases 40 --gpu 0 --fanout='35,35' --batch-size 64 --n-hidden 16 --use-self-loop --n-epochs=20 --dropout 0.7

Entity Classification on multiple GPUs

To use multiple GPUs, replace entity_sample.py with entity_sample_multi_gpu.py and specify multiple GPU IDs separated by comma, e.g., --gpu 0,1.

Link Prediction

FB15k-237 in RAW-MRR

python link.py --gpu 0 --eval-protocol raw

FB15k-237 in Filtered-MRR

python link.py --gpu 0 --eval-protocol filtered