Download scripts/validate_dataset.py from ulamai/AIME-Plus-Plus: direct link, hf CLI and curl.
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https://huggingface.co/datasets/ulamai/AIME-Plus-Plus/resolve/main/scripts/validate_dataset.py
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hf download hf://datasets/ulamai/AIME-Plus-Plus/scripts/validate_dataset.py
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7.59 kB
| #!/usr/bin/env python3 | |
| """Validate the AIME++ sample using only the Python standard library.""" | |
| from __future__ import annotations | |
| import argparse | |
| import hashlib | |
| import json | |
| import re | |
| import sys | |
| from dataclasses import dataclass | |
| from pathlib import Path | |
| ROOT = Path(__file__).resolve().parents[1] | |
| FIELDS = {"id", "problem", "answer", "answer_str", "tier"} | |
| class FileSpec: | |
| path: str | |
| tier: str | |
| id_stem: str | |
| expected_count: int | |
| FILE_SPECS = ( | |
| FileSpec("data/aime.jsonl", "AIME", "aime", 34), | |
| FileSpec("data/aime-hard.jsonl", "AIME Hard", "hard", 98), | |
| FileSpec("data/aime-graduate.jsonl", "AIME-Graduate", "graduate", 20), | |
| FileSpec("data/aime-researcher.jsonl", "AIME-Researcher", "researcher", 5), | |
| ) | |
| def normalized_problem(problem: str) -> str: | |
| return re.sub(r"\s+", " ", problem).strip().casefold() | |
| def sha256(path: Path) -> str: | |
| digest = hashlib.sha256() | |
| with path.open("rb") as handle: | |
| for chunk in iter(lambda: handle.read(1024 * 1024), b""): | |
| digest.update(chunk) | |
| return digest.hexdigest() | |
| def validate(root: Path) -> tuple[list[dict[str, object]], list[str]]: | |
| errors: list[str] = [] | |
| stats: list[dict[str, object]] = [] | |
| seen_ids: set[str] = set() | |
| seen_problems: dict[str, str] = {} | |
| for spec in FILE_SPECS: | |
| path = root / spec.path | |
| if not path.is_file(): | |
| errors.append(f"missing file: {spec.path}") | |
| continue | |
| records: list[dict[str, object]] = [] | |
| with path.open(encoding="utf-8") as handle: | |
| for line_number, line in enumerate(handle, start=1): | |
| if not line.strip(): | |
| errors.append(f"{spec.path}:{line_number}: blank lines are not allowed") | |
| continue | |
| try: | |
| record = json.loads(line) | |
| except json.JSONDecodeError as exc: | |
| errors.append(f"{spec.path}:{line_number}: invalid JSON: {exc.msg}") | |
| continue | |
| if not isinstance(record, dict): | |
| errors.append(f"{spec.path}:{line_number}: record must be an object") | |
| continue | |
| records.append(record) | |
| if len(records) != spec.expected_count: | |
| errors.append( | |
| f"{spec.path}: expected {spec.expected_count} records, found {len(records)}" | |
| ) | |
| lengths: list[int] = [] | |
| for index, record in enumerate(records, start=1): | |
| where = f"{spec.path}:{index}" | |
| if set(record) != FIELDS: | |
| missing = sorted(FIELDS - set(record)) | |
| extra = sorted(set(record) - FIELDS) | |
| errors.append(f"{where}: schema mismatch; missing={missing}, extra={extra}") | |
| continue | |
| record_id = record["id"] | |
| expected_id = f"aimepp-{spec.id_stem}-{index:04d}" | |
| if record_id != expected_id: | |
| errors.append(f"{where}: expected id {expected_id!r}, found {record_id!r}") | |
| if not isinstance(record_id, str): | |
| errors.append(f"{where}: id must be a string") | |
| elif record_id in seen_ids: | |
| errors.append(f"{where}: duplicate id {record_id!r}") | |
| else: | |
| seen_ids.add(record_id) | |
| if record["tier"] != spec.tier: | |
| errors.append(f"{where}: expected tier {spec.tier!r}") | |
| problem = record["problem"] | |
| if not isinstance(problem, str) or not problem.strip(): | |
| errors.append(f"{where}: problem must be non-empty text") | |
| else: | |
| lengths.append(len(problem)) | |
| if problem != problem.strip(): | |
| errors.append(f"{where}: problem has leading or trailing whitespace") | |
| if any(ord(character) < 32 for character in problem): | |
| errors.append(f"{where}: problem contains an ASCII control character") | |
| if problem.count("$") % 2: | |
| errors.append(f"{where}: problem has unbalanced dollar-sign LaTeX delimiters") | |
| normalized = normalized_problem(problem) | |
| if normalized in seen_problems: | |
| errors.append( | |
| f"{where}: normalized duplicate of {seen_problems[normalized]}" | |
| ) | |
| else: | |
| seen_problems[normalized] = where | |
| answer = record["answer"] | |
| if isinstance(answer, bool) or not isinstance(answer, int) or not 0 <= answer <= 999: | |
| errors.append(f"{where}: answer must be an integer in 0..999") | |
| elif record["answer_str"] != f"{answer:03d}": | |
| errors.append(f"{where}: answer_str must equal the zero-padded answer") | |
| stats.append( | |
| { | |
| "path": spec.path, | |
| "tier": spec.tier, | |
| "count": len(records), | |
| "min_chars": min(lengths) if lengths else 0, | |
| "max_chars": max(lengths) if lengths else 0, | |
| "mean_chars": round(sum(lengths) / len(lengths), 1) if lengths else 0, | |
| "sha256": sha256(path), | |
| } | |
| ) | |
| checksums_path = root / "CHECKSUMS.sha256" | |
| if not checksums_path.is_file(): | |
| errors.append("missing file: CHECKSUMS.sha256") | |
| else: | |
| declared: dict[str, str] = {} | |
| for line_number, line in enumerate( | |
| checksums_path.read_text(encoding="utf-8").splitlines(), start=1 | |
| ): | |
| match = re.fullmatch(r"([0-9a-f]{64}) (data/[^\s]+\.jsonl)", line) | |
| if not match: | |
| errors.append(f"CHECKSUMS.sha256:{line_number}: malformed checksum line") | |
| continue | |
| declared[match.group(2)] = match.group(1) | |
| expected_paths = {spec.path for spec in FILE_SPECS} | |
| if set(declared) != expected_paths: | |
| errors.append("CHECKSUMS.sha256: file list does not match the release data files") | |
| for row in stats: | |
| path = str(row["path"]) | |
| if declared.get(path) != row["sha256"]: | |
| errors.append(f"CHECKSUMS.sha256: digest mismatch for {path}") | |
| return stats, errors | |
| def print_markdown(stats: list[dict[str, object]]) -> None: | |
| print("| Tier | Records | Min chars | Mean chars | Max chars |") | |
| print("|---|---:|---:|---:|---:|") | |
| for row in stats: | |
| print( | |
| f"| {row['tier']} | {row['count']} | {row['min_chars']} | " | |
| f"{row['mean_chars']} | {row['max_chars']} |" | |
| ) | |
| print(f"\n**Total:** {sum(int(row['count']) for row in stats)} records") | |
| def main() -> int: | |
| parser = argparse.ArgumentParser(description=__doc__) | |
| parser.add_argument("--root", type=Path, default=ROOT, help="dataset repository root") | |
| parser.add_argument("--markdown", action="store_true", help="print a Markdown statistics table") | |
| args = parser.parse_args() | |
| stats, errors = validate(args.root.resolve()) | |
| if errors: | |
| print(f"FAILED: {len(errors)} validation error(s)", file=sys.stderr) | |
| for error in errors: | |
| print(f"- {error}", file=sys.stderr) | |
| return 1 | |
| if args.markdown: | |
| print_markdown(stats) | |
| else: | |
| total = sum(int(row["count"]) for row in stats) | |
| print(f"PASS: {total} records across {len(stats)} tiers") | |
| for row in stats: | |
| print(f"- {row['path']}: {row['count']} records; sha256={row['sha256']}") | |
| return 0 | |
| if __name__ == "__main__": | |
| raise SystemExit(main()) | |