File size: 2,315 Bytes
54c192e | 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 | """Score named typed answers for Structured State Reasoning Probe."""
import argparse
import json
from pathlib import Path
def load_jsonl(path):
return [json.loads(line) for line in Path(path).read_text().splitlines() if line.strip()]
def normalize(spec, raw):
if spec["type"] == "choice":
return raw.get("choice") if isinstance(raw, dict) else raw
if spec["type"] == "noul":
if isinstance(raw, bool):
return raw
if isinstance(raw, dict) and isinstance(raw.get("noul"), (int, float)):
return raw["noul"] >= 0.5
return None
def main():
parser = argparse.ArgumentParser()
parser.add_argument("predictions", help="JSONL rows: task_id and answers map")
parser.add_argument("--dataset", default=str(Path(__file__).resolve().parent / "test.jsonl"))
args = parser.parse_args()
dataset = load_jsonl(args.dataset)
predictions = load_jsonl(args.predictions)
tasks = {row["task_id"]: row for row in dataset}
pred = {row["task_id"]: row for row in predictions}
if len(tasks) != len(dataset) or len(pred) != len(predictions):
raise SystemExit("Duplicate task_id in data or predictions")
if set(tasks) != set(pred):
raise SystemExit(f"Prediction coverage mismatch: missing={sorted(set(tasks)-set(pred))}, extra={sorted(set(pred)-set(tasks))}")
task_pass = question_correct = question_total = 0
per_task = []
for tid, row in tasks.items():
questions = json.loads(row["questions_json"])
gold = json.loads(row["gold_json"])
answers = pred[tid]["answers"]
if set(answers) != set(questions):
raise SystemExit(f"Question coverage mismatch for {tid}")
checks = {qid: normalize(spec, answers[qid]) == gold[qid] for qid, spec in questions.items()}
passed = all(checks.values())
task_pass += passed
question_correct += sum(checks.values())
question_total += len(checks)
per_task.append({"task_id": tid, "pass": passed, "questions": checks})
print(json.dumps({"tasks_passed": task_pass, "tasks_total": len(tasks),
"questions_correct": question_correct, "questions_total": question_total,
"per_task": per_task}, indent=2))
if __name__ == "__main__":
main()
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