Download tasks/cpu-decoder-graph-executor/tests/finalize.py from bespokelabs/AutoResearchExam: direct link, hf CLI and curl.
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2.38 kB
| """Final verifier: score the run from the grader ledger. | |
| reward hidden test score of the submission with the best validation score | |
| (ties go to the earlier submission); 0 if nothing was submitted. | |
| auarc area under the curve of that same quantity over the wall-clock budget, | |
| using the time each validation score became available, divided by the | |
| budget. 0 before the first graded submission. | |
| """ | |
| import json | |
| from pathlib import Path | |
| STATE = Path("/var/lib/are") | |
| OUT = Path("/logs/verifier") | |
| OUT.mkdir(parents=True, exist_ok=True) | |
| meta = json.loads((STATE / "meta.json").read_text()) if (STATE / "meta.json").exists() else {} | |
| budget = float(meta.get("budget_seconds") or 1.0) | |
| subs: dict[int, dict] = {} | |
| ledger = STATE / "ledger.jsonl" | |
| for line in (ledger.read_text().splitlines() if ledger.exists() else []): | |
| ev = json.loads(line) | |
| s = subs.setdefault(ev["id"], {"id": ev["id"]}) | |
| if ev["event"] == "submitted": | |
| s["submitted_t"] = ev["t"] | |
| elif ev["event"] == "val": | |
| s["val"] = ev["score"] | |
| s["val_t"] = ev["t"] | |
| elif ev["event"] == "test": | |
| s["test"] = ev["score"] | |
| graded = sorted((s for s in subs.values() if "val" in s), key=lambda s: s["val_t"]) | |
| # Step function of the hidden score of the best-validation pick over time. | |
| auc, best, last_t, cur = 0.0, None, 0.0, 0.0 | |
| timeline = [] | |
| for s in graded: | |
| t = min(s["val_t"], budget) | |
| auc += cur * (t - last_t) | |
| last_t = t | |
| if best is None or s["val"] > best["val"] or (s["val"] == best["val"] and s["id"] < best["id"]): | |
| best = s | |
| cur = float(best.get("test") or 0.0) | |
| timeline.append({"t": s["val_t"], "id": s["id"], "val": s["val"], "test": s.get("test"), | |
| "pick": best["id"]}) | |
| auc += cur * (budget - last_t) if last_t < budget else 0.0 | |
| reward = { | |
| "reward": float(best.get("test") or 0.0) if best else 0.0, | |
| "auarc": auc / budget, | |
| "best_val": float(best["val"]) if best else 0.0, | |
| "n_submissions": float(len(subs)), | |
| "n_test_graded": float(sum(s.get("test") is not None for s in subs.values())), | |
| } | |
| (OUT / "reward.json").write_text(json.dumps(reward)) | |
| (OUT / "timeline.json").write_text(json.dumps({"budget": budget, "selected": best and best["id"], | |
| "submissions": timeline}, indent=1)) | |
| print(json.dumps(reward, indent=1)) | |