#!/bin/bash source ~/anaconda3/etc/profile.d/conda.sh conda activate pytorch_p38 python train.py --model_name hgvp \ --accelerator gpu \ --devices 1 \ --max_epochs 500 \ --precision 32 \ --num_layers 3 \ --node_h_dim 200 32 \ --edge_h_dim 64 2 \ --dataset_name PDBBind \ --input_type complex \ --data_dir /home/ec2-user/SageMaker/efs/data/PIGNet/data/pdbbind_v2019_processed/scoring \ --residual \ --num_workers 8 \ --lr 1e-4 \ --bs 8 \ --early_stopping_patience 10 \ --residue_featurizer_name MolT5-small-grad \ --default_root_dir /home/ec2-user/SageMaker/efs/model_logs/zichen/PDBBind_GVP_MolT5_grad python train.py --model_name hgvp \ --accelerator gpu \ --devices 4 \ --max_epochs 500 \ --precision 32 \ --num_layers 3 \ --node_h_dim 200 32 \ --edge_h_dim 64 2 \ --dataset_name PDBBind \ --input_type complex \ --data_dir /home/ec2-user/SageMaker/efs/data/PIGNet/data/pdbbind_v2019_processed/scoring \ --residual \ --num_workers 8 \ --lr 1e-4 \ --bs 4 \ --early_stopping_patience 200 \ --residue_featurizer_name MolT5-small-grad \ --default_root_dir /home/ec2-user/SageMaker/efs/model_logs/zichen/PDBBind_GVP_MolT5_grad python evaluate_casf2016.py --model_name hgvp \ --num_workers 8 \ --data_dir /home/ec2-user/SageMaker/efs/data/PIGNet/data/casf2016_processed \ --checkpoint_path /home/ec2-user/SageMaker/efs/model_logs/zichen/PDBBind_GVP_MolT5_grad/lightning_logs/version_23 \ --residue_featurizer_name MolT5-small-grad ## PDBBind bin-clf python train.py --model_name hgvp \ --accelerator gpu \ --devices 4 \ --max_epochs 500 \ --precision 32 \ --num_layers 3 \ --node_h_dim 200 32 \ --edge_h_dim 64 2 \ --dataset_name PDBBind \ --input_type complex \ --data_dir /home/ec2-user/SageMaker/efs/data/PIGNet/data/pdbbind_v2019_processed/scoring \ --residual \ --num_workers 8 \ --lr 1e-5 \ --bs 4 \ --early_stopping_patience 10 \ --residue_featurizer_name MolT5-small-grad \ --default_root_dir /home/ec2-user/SageMaker/efs/model_logs/zichen/PDBBind_bin_GVP_MolT5_grad \ --binary_cutoff 6.7