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Download klein_code_bench/scoring.py from klein-ml/klein-code-bench: direct link, hf CLI and curl.
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https://huggingface.co/datasets/klein-ml/klein-code-bench/resolve/main/klein_code_bench/scoring.py
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hf download hf://datasets/klein-ml/klein-code-bench/klein_code_bench/scoring.py
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curl -L -o scoring.py https://huggingface.co/datasets/klein-ml/klein-code-bench/resolve/main/klein_code_bench/scoring.py
1.5 kB
| """Strict all-tests-pass scoring; partial assertions are diagnostics only.""" | |
| from .protocol import TIERS | |
| def summarize(reports): | |
| from .runner import load_tasks | |
| catalog = {t["task_id"]: t for t in load_tasks()} | |
| seen = set() | |
| buckets = {tier: [] for tier in TIERS} | |
| for report in reports: | |
| task_id = report["task_id"] | |
| if task_id in seen: | |
| raise ValueError(f"Duplicate task report: {task_id}") | |
| seen.add(task_id) | |
| if task_id not in catalog or report.get("subset") != catalog[task_id]["subset"]: | |
| raise ValueError(f"Unknown task or mismatched subset: {task_id}") | |
| if report.get("evaluation_scope") == "public": | |
| raise ValueError("Public-only smoke tests cannot be scored") | |
| buckets[report["subset"]].append(report.get("resolved") is True) | |
| tiers = {} | |
| for tier, statuses in buckets.items(): | |
| resolved = sum(statuses) | |
| tiers[tier] = { | |
| "submitted": len(statuses), | |
| "total": 65, | |
| "resolved": resolved, | |
| "resolution_rate": resolved / 65, | |
| "submitted_resolution_rate": resolved / len(statuses) if statuses else None, | |
| } | |
| return { | |
| "metric": "resolve@1", | |
| "total": 260, | |
| "submitted": len(seen), | |
| "resolved": sum(r["resolved"] for r in tiers.values()), | |
| "resolution_rate": sum(r["resolved"] for r in tiers.values()) / 260, | |
| "complete": len(seen) == 260, | |
| "subsets": tiers, | |
| } | |