dmlc--dgl
0227ddfb66
* WIP: TypedLinear and new RelGraphConv * wip * further simplify RGCN * a bunch of tweak for performance; add basic cpu support * update on segmm * wip: segment.cu * new backward kernel works * fix a bunch of bugs in kernel; leave idx_a for future * add nn test for typed_linear * rgcn nn test * bugfix in corner case; update RGCN README * doc * fix cpp lint * fix lint * fix ut * wip: hgtconv; presorted flag for rgcn * hgt code and ut; WIP: some fix on reorder graph * better typed linear init * fix ut * fix lint; add docstring
1.7 KiB
1.7 KiB
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