| |
| """Test gate for final packaging (Yeepee, Huawei TechArena 2026 CTR). |
| |
| A submission is zipped as FINAL only if its local test score reaches the bar |
| (default 0.83) on the primary cut C=25 (staleness-reweighted AUC when given, |
| otherwise overall AUC) AND it passes the format checks. Otherwise nothing is |
| written and the script exits with code 1. |
| |
| Usage: |
| python3 package_final.py --csv sub.csv --metrics metrics.json [--name v10] [--bar 0.83] |
| python3 package_final.py --csv sub.csv --auc25 0.8312 [--rw25 0.8305] |
| |
| metrics.json: either {"cut":25,"auc":..,"rw":..} or a list / jsonl of such rows |
| (the row with cut 25 is used). |
| """ |
| import argparse, hashlib, json, math, os, sys, zipfile |
| import pandas as pd |
|
|
| REF = "/workspace/huawei/data/evaluation.csv" |
| N_ROWS = 529390 |
|
|
| def load_c25(path): |
| txt = open(path).read().strip() |
| rows = [] |
| try: |
| j = json.loads(txt); rows = j if isinstance(j, list) else [j] |
| except json.JSONDecodeError: |
| rows = [json.loads(l) for l in txt.splitlines() if l.strip()] |
| c25 = [r for r in rows if int(r.get("cut", 25)) == 25] |
| if not c25: |
| sys.exit("GATE FAIL: no C=25 row in metrics file") |
| return c25[-1] |
|
|
| def num(x): |
| try: |
| x = float(x); return None if math.isnan(x) else x |
| except (TypeError, ValueError): |
| return None |
|
|
| def main(): |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--csv", required=True) |
| ap.add_argument("--metrics"); ap.add_argument("--auc25", type=float); ap.add_argument("--rw25", type=float) |
| ap.add_argument("--bar", type=float, default=0.83) |
| ap.add_argument("--name"); ap.add_argument("--outdir") |
| a = ap.parse_args() |
|
|
| if a.metrics: |
| r = load_c25(a.metrics); auc, rw = num(r.get("auc")), num(r.get("rw")) |
| else: |
| auc, rw = a.auc25, a.rw25 |
| score = rw if rw is not None else auc |
| if score is None: |
| sys.exit("GATE FAIL: no local C=25 score given; refusing to package") |
| label = "C=25 reweighted AUC" if rw is not None else "C=25 AUC" |
| print(f"{label}: {score:.5f} (bar {a.bar})") |
| if score < a.bar: |
| print(f"GATE FAIL: {score:.5f} < {a.bar}. Not packaged."); sys.exit(1) |
|
|
| df = pd.read_csv(a.csv) |
| errs = [] |
| if list(df.columns) != ["rowid", "predicted_probability"]: errs.append(f"columns {list(df.columns)}") |
| if len(df) != N_ROWS: errs.append(f"{len(df)} rows, expected {N_ROWS}") |
| if df["rowid"].duplicated().any(): errs.append("duplicate rowids") |
| p = df["predicted_probability"] |
| if p.isna().any() or (p < 0).any() or (p > 1).any(): errs.append("probabilities missing or outside [0,1]") |
| if os.path.exists(REF): |
| ref = pd.read_csv(REF, usecols=["rowid"])["rowid"] |
| if set(ref) != set(df["rowid"]): errs.append("rowid set differs from eval set") |
| if errs: |
| print("GATE FAIL (format): " + "; ".join(errs)); sys.exit(1) |
|
|
| name = a.name or os.path.splitext(os.path.basename(a.csv))[0] |
| outdir = a.outdir or os.path.dirname(os.path.abspath(a.csv)) |
| zp = os.path.join(outdir, f"{name}_FINAL.csv.zip") |
| with zipfile.ZipFile(zp, "w", zipfile.ZIP_DEFLATED) as z: |
| z.write(a.csv, arcname=f"{name}.csv") |
| sha = hashlib.sha256(open(zp, "rb").read()).hexdigest() |
| with open(zp + ".gate.json", "w") as f: |
| json.dump({"csv": os.path.abspath(a.csv), "zip": zp, "sha256": sha, "score_c25": score, |
| "metric": label, "bar": a.bar, "auc25": auc, "rw25": rw}, f, indent=1) |
| print(f"GATE PASS: packaged {zp}\nsha256 {sha}") |
|
|
| if __name__ == "__main__": |
| main() |
|
|
