Use several GNN models for benchmarking biomedical dataset.
Used GNN models:
- GCN
- GAT
- GCNII
Run training process in Google Colab
- Install dependencies
!pip install torch-scatter torch-sparse torch-cluster torch-spline-conv torch-geometric -f https://data.pyg.org/whl/torch-1.11.0+cu113.html
!pip install -q wandb
!pip install igraph
- Login to wandb
!wandb login
- Run training with configuration via env vars and cli flags, e.g.
%env MODEL=gcn2
%env ROOT=/gdrive/MyDrive/GNN/KidneyMetabolic_deg
%env TYPE=kidney_metabolic
!for i in $(seq 1 5); do python train.py --weighted --test_run -b 64 -e 200 -v 0.3 -m "$MODEL" -y 64 32 --conv_num 16 --test_ratio 0.2 --conv_pooling "mean" -r "$ROOT" -t "$TYPE"; done
!python eval.py --file "test_metric.json"