import os

def run(cmd):
    print("\n======================================")
    print("Running command:")
    print(cmd)
    print("======================================\n")
    os.system(cmd)

def generate_features(data_path, save_path):
    run(
        f"python scripts/save_features.py "
        f"--data_path {data_path} "
        f"--save_path {save_path} "
        f"--features_generator rdkit_2d_normalized "
        f"--restart"
    )

def predict_from_csv(data_path, features_path, checkpoint_dir, output_path):
    predict_cmd = (
        f"python main.py predict "
        f"--data_path {data_path} "
        f"--features_path {features_path} "
        f"--checkpoint_dir {checkpoint_dir} "
        f"--no_features_scaling "
        f"--output {output_path}"
    )
    run(predict_cmd)


def finetune(train_path, val_path, train_features_path, val_features_path, 
        save_dir, checkpoint_path, args
    ):
    finetune_cmd = (
        f"python main.py finetune "
        f"--data_path {train_path} "
        f"--split_type random "
        f"--split_sizes 1 0 0 "
        f"--separate_val_path {val_path} "
        f"--separate_test_path {val_path} "
        f"--features_path {train_features_path} "
        f"--separate_val_features_path {val_features_path} "
        f"--separate_test_features_path {val_features_path} "
        f"--save_dir {save_dir} "
        f"--checkpoint_path {checkpoint_path} "
        f"--dataset_type classification "
        f"--num_folds 1 "
        f"--ensemble_size 1 "
        f"--no_features_scaling "
        f"--ffn_hidden_size {args['ffn_hidden_size']} "
        f"--ffn_num_layers {args['ffn_num_layer']} "
        f"--batch_size {args['batch_size']} "
        f"--epochs 100 "
        f"--init_lr {args['real_init_lr']} "
        f"--final_lr {args['real_final_lr']} "
        f"--max_lr {args['max_lr']} "
        f"--dropout {args['dropout']} "
        f"--attn_hidden {args['attn_hidden']} "
        f"--attn_out {args['attn_out']} "
        f"--dist_coff {args['dist_coff']} "
        f"--bond_drop_rate {args['bond_drop_rate']} "
    )
    run(finetune_cmd)