| """Turn bench result files into the Hugging Face dataset folder. |
| |
| python3 build_dataset.py OUT_DIR results/*.jsonl |
| |
| Writes, under OUT_DIR: |
| data/cases.jsonl one row per case-run (the table most people want) |
| data/calls.jsonl one row per model request |
| data/runs.jsonl one row per bench invocation (model, settings, versions) |
| raw/<label>.jsonl the bench's own files, unchanged except for scrubbed local paths |
| summary/ summarize.py's tables over everything |
| code/ the bench, the summarizer, the Kaggle runner and this script |
| |
| Nested fields (input, expected, output, mismatches, path, ...) are stored as JSON strings in |
| data/, so every row of a table has the same columns and types. Hugging Face's viewer and |
| `datasets.load_dataset` both need that; the raw/ files keep the original shapes. |
| """ |
|
|
| import json |
| import os |
| import re |
| import shutil |
| import subprocess |
| import sys |
|
|
| HERE = os.path.dirname(os.path.abspath(__file__)) |
| KAGGLE_RUNNER = os.path.join(HERE, "kaggle_runner.py") |
|
|
| |
| |
| LOCAL_PATH = re.compile(r"/(?:Users|home)/[^\"\s]+") |
|
|
| NESTED = { |
| "case": ("input", "expected", "output", "mismatches", "path", "gates", "escalations", |
| "rescued_expected"), |
| "call": ("output",), |
| "run": ("arms", "packs", "extra_body", "setup", "pack_digests", "stepmold", "bench"), |
| } |
|
|
|
|
| def scrub(text): |
| return LOCAL_PATH.sub("<local checkout>", text) |
|
|
|
|
| def flatten(record): |
| row = dict(record) |
| for key in NESTED.get(record.get("kind"), ()): |
| if key in row and row[key] is not None and not isinstance(row[key], str): |
| row[key] = json.dumps(row[key], sort_keys=True) |
| return row |
|
|
|
|
| def main(out, files): |
| for sub in ("data", "raw", "summary", "code"): |
| os.makedirs(os.path.join(out, sub), exist_ok=True) |
| tables = {"case": [], "call": [], "run": []} |
| for path in files: |
| label = os.path.splitext(os.path.basename(path))[0] |
| with open(path) as handle, open(os.path.join(out, "raw", label + ".jsonl"), "w") as raw: |
| for line in handle: |
| line = scrub(line) |
| raw.write(line) |
| record = json.loads(line) |
| if record.get("kind") in tables: |
| tables[record["kind"]].append(flatten(record)) |
| names = {"case": "cases", "call": "calls", "run": "runs"} |
| for kind, rows in tables.items(): |
| with open(os.path.join(out, "data", names[kind] + ".jsonl"), "w") as handle: |
| for row in rows: |
| handle.write(json.dumps(row, sort_keys=True) + "\n") |
| print("%-6s %6d rows" % (names[kind], len(rows))) |
|
|
| subprocess.run([sys.executable, os.path.join(HERE, "summarize.py")] + list(files), check=True, |
| stdout=subprocess.DEVNULL) |
| for name in ("summary.md", "summary.csv"): |
| shutil.move(os.path.join(os.path.dirname(files[0]), name), os.path.join(out, "summary", name)) |
| for name in ("bench.py", "summarize.py", "build_dataset.py", "README.md"): |
| shutil.copy(os.path.join(HERE, name), os.path.join(out, "code", name)) |
| if os.path.exists(KAGGLE_RUNNER): |
| shutil.copy(KAGGLE_RUNNER, os.path.join(out, "code", "kaggle_runner.py")) |
|
|
| leaks = [p for p in (os.path.join(dp, f) for dp, _, fs in os.walk(out) for f in fs) |
| if LOCAL_PATH.search(open(p, errors="ignore").read()) and "/code/" not in p] |
| print("local paths left outside code/:", leaks or "none") |
|
|
|
|
| if __name__ == "__main__": |
| if len(sys.argv) < 3: |
| sys.exit(__doc__) |
| main(sys.argv[1], sys.argv[2:]) |
|
|
