from __future__ import annotations

import argparse
import sys
from pathlib import Path

ROOT_DIR = Path(__file__).resolve().parents[1]
if str(ROOT_DIR) not in sys.path:
    sys.path.insert(0, str(ROOT_DIR))

from lib.trainers import build_trainer
from lib.utils.config import apply_dotlist_overrides, load_yaml_config


def parse_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser(description="Unified training entrypoint.")
    parser.add_argument(
        "--config",
        type=str,
        required=True,
        help="Path to yaml config.",
    )
    parser.add_argument(
        "--trainer",
        type=str,
        default=None,
        help="Override trainer name from config.",
    )
    parser.add_argument(
        "--set",
        nargs="*",
        default=None,
        help="Override config values with key=value pairs, e.g. train.epochs=2 model.use_wavelet_branch=false",
    )
    return parser.parse_args()


def main() -> None:
    args = parse_args()
    cfg_path = ROOT_DIR / args.config if not Path(args.config).is_absolute() else Path(args.config)
    cfg = load_yaml_config(cfg_path)
    cfg = apply_dotlist_overrides(cfg, args.set)

    if args.trainer is not None:
        cfg.setdefault("trainer", {})
        cfg["trainer"]["name"] = args.trainer

    trainer = build_trainer(cfg, args=args)
    trainer.train()


if __name__ == "__main__":
    main()