import argparse

from as_mamba import TrainConfig, run_training_and_plot


def build_parser() -> argparse.ArgumentParser:
    parser = argparse.ArgumentParser(description="Train AS-Mamba on sphere-to-sphere flow.")
    parser.add_argument("--epochs", type=int, default=None)
    parser.add_argument("--warmup-epochs", type=int, default=None)
    parser.add_argument("--batch-size", type=int, default=None)
    parser.add_argument("--steps-per-epoch", type=int, default=None)
    parser.add_argument("--seq-len", type=int, default=None)
    parser.add_argument("--lr", type=float, default=None)
    parser.add_argument("--device", type=str, default=None)
    parser.add_argument("--output-dir", type=str, default=None)
    parser.add_argument("--project", type=str, default=None)
    parser.add_argument("--run-name", type=str, default=None)
    parser.add_argument("--val-every", type=int, default=None)
    parser.add_argument("--val-samples", type=int, default=None)
    parser.add_argument("--val-plot-samples", type=int, default=None)
    parser.add_argument("--val-max-steps", type=int, default=None)
    parser.add_argument("--center-min", type=float, default=None)
    parser.add_argument("--center-max", type=float, default=None)
    parser.add_argument("--center-distance-min", type=float, default=None)
    parser.add_argument("--use-residual", action="store_true")
    return parser


def main() -> None:
    parser = build_parser()
    args = parser.parse_args()

    cfg = TrainConfig()
    for key, value in vars(args).items():
        if value is not None:
            setattr(cfg, key.replace("-", "_"), value)

    plot_path = run_training_and_plot(cfg)
    print(f"Saved trajectory plot to {plot_path}")


if __name__ == "__main__":
    main()