To train:
python train.py --dataroot /home/sunhwan/work/pdbbind/2018/refined-set \
--csvfile /home/sunhwan/work/pdbbind/deep/data/train.csv \
--gpu_ids 0 --batch_size 64 --nThreads 16 --init_type kaiming \
--lr 0.0001 --niter 50 --niter_decay 25 --save_epoch_freq 5 \
--model kdeep --grid_method kdeep --grid_size 24 --grid_spacing 1.0 \
--channels kdeep --rvdw 2
add --continue-train
to resume training from the latest weight.
To test:
python test.py --dataroot /home/sunhwan/work/pdbbind/2018/refined-set \
--csvfile /home/sunhwan/work/pdbbind/deep/data/test.csv \
--gpu_ids 0 --batch_size 64 --nThreads 16 \
--model kdeep --grid_method kdeep --grid_size 24 --grid_spacing 1.0 \
--channels kdeep --rvdw 2
To train:
python train.py --dataroot /home/sunhwan/work/pdbbind/2018/refined-set \
--csvfile /home/sunhwan/work/pdbbind/deep/data/train.csv \
--gpu_ids 0 --batch_size 32 --nThreads 16 --init_type kaiming \
--lr 0.0001 --niter 50 --niter_decay 25 --save_epoch_freq 5 \
--model gnina --grid_method gnina --grid_size 48 --grid_spacing 0.5 \
--channels gnina
add --continue-train
to resume training from the latest weight.
To test:
python test.py --dataroot /home/sunhwan/work/pdbbind/2018/refined-set \
--csvfile /home/sunhwan/work/pdbbind/deep/data/test.csv \
--gpu_ids 0 --batch_size 32 --nThreads 16 \
--model gnina --grid_method gnina --grid_size 48 --grid_spacing 0.5 \
--channels gnina
To train:
python train.py --dataroot /home/sunhwan/work/pdbbind/2018/refined-set \
--csvfile /home/sunhwan/work/pdbbind/deep/data/train.csv \
--gpu_ids 0 --batch_size 32 --nThreads 16 --init_type kaiming \
--lr 0.0001 --niter 50 --niter_decay 25 --save_epoch_freq 5 \
--model gnina_docked --grid_method gnina_docked --grid_size 48 \
--grid_spacing 0.5 --channels gnina --dataset_mode pdbbind_docked
add --continue-train
to resume training from the latest weight.
To test:
python test.py --dataroot /home/sunhwan/work/pdbbind/2018/refined-set \
--csvfile /home/sunhwan/work/pdbbind/deep/data/test.csv \
--gpu_ids 0 --batch_size 32 --nThreads 16 \
--model gnina --grid_method gnina --grid_size 48 --grid_spacing 0.5 \
--channels gnina
To make reading data faster, use the following command to preprocess PDB/Mol2 files and determine Smina atom types prior to training.
python data.py --dataroot /home/sunhwan/work/pdbbind/2018/refined-set
python data.py --dataroot /home/sunhwan/work/pdbbind/2018/other-set