import torch

from src.args import parse_arguments
from src.process import compress
from src.train import train


def main():
    args, print_help = parse_arguments()

    if torch.accelerator.is_available():
        device = torch.accelerator.current_accelerator().type
    else:
        device = "cpu"
    print(f"Running on device: {device}...")

    match args.mode:
        case 'train':
            train(
                device=device,
                dataset=args.dataset,
                data_root=args.data_root,
                n_trials=3 if args.debug else None,
                size=2 ** 10 if args.debug else None,
                method=args.method,
                model_name=args.model,
                model_path=args.model_load_path,
                model_out=args.model_save_path
            )

        case 'compress':
            compress(device=device,
                     model_path=args.model_load_path,
                     input_file=args.input_file,
                     output_file=args.output_file
                     )

        case _:
            raise NotImplementedError(f"Mode {args.mode} is not implemented yet")

    print("Done")


if __name__ == "__main__":
    main()