/examples/pytorch/mock_sparse/rgcn-hetero

Relation-GCN

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• Paper: https://arxiv.org/abs/1703.06103
• Author's code for entity classification: https://github.com/tkipf/relational-gcn
• Author's code for link prediction: https://github.com/MichSchli/RelationPrediction

How to run

Run with the following (available dataset: "aifb", "mutag", "bgs", "am")

python3 entity_classify.py --dataset aifb

Output

Reports training accuracy and loss after each epoch and test accuracy in the end.

Epoch 00000 | Train Acc: 0.3000 | Train Loss: 7.2665 | Valid Acc: 0.3000 | Valid loss: 7.2665
Epoch 00001 | Train Acc: 0.4571 | Train Loss: 2.1582 | Valid Acc: 0.4571 | Valid loss: 2.1582
Epoch 00002 | Train Acc: 0.7071 | Train Loss: 1.0288 | Valid Acc: 0.7071 | Valid loss: 1.0288
Epoch 00003 | Train Acc: 0.7143 | Train Loss: 0.9438 | Valid Acc: 0.7143 | Valid loss: 0.9438
...
Epoch 00048 | Train Acc: 0.7643 | Train Loss: 0.7254 | Valid Acc: 0.7643 | Valid loss: 0.7254
Epoch 00049 | Train Acc: 0.7643 | Train Loss: 0.7252 | Valid Acc: 0.7643 | Valid loss: 0.7252

Test Acc: 0.7500 | Test loss: 0.7506