File size: 2,381 Bytes
974872c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | """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))
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