"""

Resume Day 2-3 tasks SEQUENTIALLY (one heavy job at a time).



Previous crashes were likely caused by running 4 AdaptFormer/TensorFlow jobs in

parallel while also writing thousands of mask PNGs to disk.



Usage:

    python scripts/resume_day3_tasks.py

    python scripts/resume_day3_tasks.py --from grid

"""

from __future__ import annotations



import argparse

import json

import subprocess

import sys

from pathlib import Path



ROOT = Path(__file__).resolve().parent.parent

PY = sys.executable





def run_step(name: str, cmd: list[str]) -> None:

    print(f"\n{'=' * 60}\nSTEP: {name}\n{'=' * 60}")

    subprocess.run(cmd, check=True, cwd=ROOT)

    print(f"STEP DONE: {name}")





def main():

    parser = argparse.ArgumentParser(description="Resume Day 3 tasks sequentially")

    parser.add_argument("--from", dest="from_step",

                        choices=["baseline", "grid", "calibration", "finetune"],

                        default="baseline")

    parser.add_argument("--finetune-epochs", type=int, default=12)

    parser.add_argument("--force", action="store_true",

                        help="re-run steps even if output artifacts already exist")

    args = parser.parse_args()



    baseline_out = ROOT / "runs/delhi_baseline/metrics.json"

    grid_out = ROOT / "runs/calibration/best_params.json"

    calib_out = ROOT / "runs/calibration/leaderboard.json"

    finetune_glob = ROOT / "runs/finetune_adaptformer"



    steps: list[tuple[str, list[str], Path | None]] = [

        ("baseline", [PY, "scripts/record_delhi_baseline.py"], baseline_out),

        ("grid", [

            PY, "scripts/grid_search_calibration.py",

            "--manifest", "docs/delhi_eval/manifest.json",

            "--methods", "Feature-Based",

            "--sensitivities", "0.2,0.3,0.4,0.5,0.6,0.7,0.8",

            "--fusions", "smart_union,hysteresis",

            "--out", "runs/calibration/leaderboard.csv",

        ], grid_out),

        ("calibration", [

            PY, "scripts/delhi_calibration_sweep.py",

            "--manifest", "docs/delhi_eval/manifest.json",

            "--out", "runs/calibration",

            "--methods", "Feature-Based",

            "--quick",

        ], calib_out),

        ("finetune", [

            PY, "scripts/finetune_adaptformer.py",

            "--manifest", "docs/delhi_eval/manifest.json",

            "--epochs", str(args.finetune_epochs),

            "--batch-size", "2",

        ], None),

    ]



    start = False

    for name, cmd, artifact in steps:

        if name == args.from_step:

            start = True

        if not start:

            continue

        if artifact and artifact.is_file() and not args.force:

            print(f"\nSKIP {name}: {artifact} already exists (use --force to re-run)")

            continue

        if name == "finetune" and not args.force:

            existing = sorted(finetune_glob.glob("*/metrics.json"))

            if existing:

                print(f"\nSKIP finetune: {existing[-1]} already exists (use --force to re-run)")

                continue

        run_step(name, cmd)



    summary = {}

    for path, key in [

        (baseline_out, "baseline"),

        (grid_out, "calibration_best"),

        (calib_out, "calibration_leaderboard"),

        (ROOT / "runs/calibration/grid_search/manifest_report.json", "grid_search_manifest"),

    ]:

        if path.is_file():

            summary[key] = json.loads(path.read_text(encoding="utf-8"))

    finetune_runs = sorted(finetune_glob.glob("*/metrics.json"))

    if finetune_runs:

        summary["finetune"] = json.loads(finetune_runs[-1].read_text(encoding="utf-8"))



    out = ROOT / "runs/day3_completion_summary.json"

    out.parent.mkdir(parents=True, exist_ok=True)

    out.write_text(json.dumps(summary, indent=2), encoding="utf-8")

    print(f"\nAll steps finished. Summary: {out}")





if __name__ == "__main__":

    main()