| """Small, deterministic helpers for the four dataset configurations.""" |
| from __future__ import annotations |
|
|
| import hashlib |
| import json |
| from pathlib import Path |
|
|
| import pyarrow as pa |
| import pyarrow.parquet as pq |
|
|
| ROOT = Path(__file__).resolve().parents[1] |
|
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|
|
| def load_json(path): |
| return json.loads(Path(path).read_text(encoding='utf-8')) |
|
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|
|
| def write_json(path, value, *, compact=False): |
| path = Path(path) |
| path.parent.mkdir(parents=True, exist_ok=True) |
| path.write_text(json.dumps(value, ensure_ascii=False, indent=None if compact else 2, |
| separators=(',', ':') if compact else None) + '\n', encoding='utf-8') |
|
|
|
|
| def sha256(path): |
| result = hashlib.sha256() |
| with Path(path).open('rb') as handle: |
| for block in iter(lambda: handle.read(4194304), b''): |
| result.update(block) |
| return result.hexdigest() |
|
|
|
|
| def id_hash(ids): |
| return hashlib.sha256(('\n'.join(sorted(ids)) + '\n').encode()).hexdigest() |
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|
|
| def normalized_prompt(text): |
| return ' '.join(text.split()) |
|
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|
|
| def ids_from_table(table): |
| if 'problem_id' in table.column_names: |
| return table['problem_id'].to_pylist() |
| return [row['problem_id'] for row in table['extra_info'].to_pylist()] |
|
|
|
|
| def write_parquet(path, table): |
| path = Path(path) |
| path.parent.mkdir(parents=True, exist_ok=True) |
| pq.write_table(table, path, compression='zstd', row_group_size=1024) |
|
|
|
|
| def describe_file(path, root): |
| path = Path(path) |
| parquet = pq.ParquetFile(path) |
| columns = ['problem_id'] if 'problem_id' in parquet.schema_arrow.names else ['extra_info'] |
| ids = ids_from_table(parquet.read(columns=columns)) |
| return {'path': path.relative_to(root).as_posix(), 'rows': parquet.metadata.num_rows, |
| 'bytes': path.stat().st_size, 'sha256': sha256(path), |
| 'problem_id_set_sha256': id_hash(ids), 'columns': parquet.schema_arrow.names} |
|
|
|
|
| def make_manifest(root, family, split_policy): |
| files = {} |
| for kind in ['sft', 'rl']: |
| for split in ['train', 'validation']: |
| path = root / 'data' / family / kind / (split + '.parquet') |
| files[f'{kind}/{split}'] = describe_file(path, root) |
| result = {'version': '1.0.0', 'family': family, 'split_policy': split_policy, 'files': files} |
| write_json(root / 'metadata' / family / 'dataset_manifest.json', result) |
| return result |
|
|
|
|
| def member_record(ids, removed_category=None): |
| return {'rows': len(ids), 'problem_ids': ids, 'problem_id_set_sha256': id_hash(ids), |
| 'removed_category': removed_category} |
|
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|
|
| def export_rows(table, ids, destination): |
| all_ids = ids_from_table(table) |
| lookup = {v: i for i, v in enumerate(all_ids)} |
| if len(lookup) != len(all_ids): |
| raise ValueError('Duplicate source IDs') |
| missing = set(ids) - lookup.keys() |
| if missing: |
| raise ValueError(f'{len(missing)} arm IDs absent from this split') |
| write_parquet(destination, table.take(pa.array([lookup[v] for v in ids], type=pa.int64()))) |
|
|
