dmlc--dgl
Chao Ma
d57ff78da1
* API change of kvstore * add demo for kvstore * update * remove duplicated log * change queue size * update * update * update * update * update * update * update * update * update * fix lint * change name * update * fix lint * update * update * update * update * change message queue size to a python argument * change default queue size to 2GB * OMP_NUM_THREADS=1
Stochastic Training for Graph Convolutional Networks
- Paper: Control Variate
- Paper: Skip Connection
- Author's code: https://github.com/thu-ml/stochastic_gcn
Dependencies
- PyTorch 0.4.1+
- requests
bash pip install torch requests
Neighbor Sampling & Skip Connection
cora
Test accuracy ~83% with --num-neighbors 2, ~84% by training on the full graph
DGLBACKEND=pytorch python3 gcn_ns_sc.py --dataset cora --self-loop --num-neighbors 2 --batch-size 1000000 --test-batch-size 1000000
citeseer
Test accuracy ~69% with --num-neighbors 2, ~70% by training on the full graph
DGLBACKEND=pytorch python3 gcn_ns_sc.py --dataset citeseer --self-loop --num-neighbors 2 --batch-size 1000000 --test-batch-size 1000000
pubmed
Test accuracy ~76% with --num-neighbors 3, ~77% by training on the full graph
DGLBACKEND=pytorch python3 gcn_ns_sc.py --dataset pubmed --self-loop --num-neighbors 3 --batch-size 1000000 --test-batch-size 1000000
Control Variate & Skip Connection
cora
Test accuracy ~84% with --num-neighbors 1, ~84% by training on the full graph
DGLBACKEND=pytorch python3 gcn_cv_sc.py --dataset cora --self-loop --num-neighbors 1 --batch-size 1000000 --test-batch-size 1000000
citeseer
Test accuracy ~69% with --num-neighbors 1, ~70% by training on the full graph
DGLBACKEND=pytorch python3 gcn_cv_sc.py --dataset citeseer --self-loop --num-neighbors 1 --batch-size 1000000 --test-batch-size 1000000
pubmed
Test accuracy ~77% with --num-neighbors 1, ~77% by training on the full graph
DGLBACKEND=pytorch python3 gcn_cv_sc.py --dataset pubmed --self-loop --num-neighbors 1 --batch-size 1000000 --test-batch-size 1000000