export EXP=PIGNet
python -u ./train.py \
--batch_size=8 \
--save_every=100 \
--save_dir=results/$EXP \
--tensorboard_dir=runs/$EXP \
--n_gnn=3 \
--dim_gnn=128 \
--ngpu=1 \
--train_result_filename=result/"$EXP"_train.txt \
--test_result_filename=result/"$EXP"_test.txt \
--train_result_docking_filename=result/"$EXP"_train_docking.txt \
--test_result_docking_filename=result/"$EXP"_test_docking.txt \
--train_result_screening_filename=result/"$EXP"_train_screening.txt \
--test_result_screening_filename=result/"$EXP"_test_screening.txt \
--loss_der1_ratio=10.0 \
--loss_der2_ratio=10.0 \
--min_loss_der2=-20.0 \
--min_loss_docking=-1.0 \
--loss_docking_ratio=10.0 \
--loss_screening_ratio=5.0 \
--loss_screening2_ratio=5.0 \
--data_dir=./data/pdbbind_v2019/scoring/data \
--filename=./data/pdbbind_v2019/scoring/pdb_to_affinity.txt \
--key_dir=./data/pdbbind_v2019/scoring/keys \
--data_dir2=./data/pdbbind_v2019/docking/data \
--filename2=./data/pdbbind_v2019/docking/pdb_to_affinity.txt \
--key_dir2=./data/pdbbind_v2019/docking/keys \
--data_dir3=./data/pdbbind_v2019/random/data \
--filename3=./data/pdbbind_v2019/random/pdb_to_affinity.txt \
--key_dir3=./data/pdbbind_v2019/random/keys \
--data_dir4=./data/pdbbind_v2019/cross/data \
--filename4=./data/pdbbind_v2019/cross/pdb_to_affinity.txt \
--key_dir4=./data/pdbbind_v2019/cross/keys \
--num_workers=4 \
--model=pignet \
--num_epochs=3001 \
--dropout_rate=0.1 \
--interaction_net \
--dev_vdw_radius=0.2 \
1>log/$EXP.out 2>log/$EXP.err
