"""Repair the pinned vision release without reloading upstream image sources. Local inputs are the materialized base and append builds recorded in the parent release. Without those caches, load the pinned Hub config and separate its original and appended rows using the published split counts. """ import copy import hashlib import json import re import subprocess import sys from collections import Counter from pathlib import Path import pyarrow as pa import pyarrow.parquet as pq import yaml from datasets import Dataset, DatasetDict, load_dataset, load_from_disk, disable_progress_bars from huggingface_hub import HfApi, hf_hub_download, DatasetCard, CommitOperationAdd from scripts.build_jev_dataset import example_key, validate_decisions from tasksource.licenses import source_license, provenance_repos from tasksource.vision_tasks import clean_cauldron_question ROOT = Path('build/vision-prompt-license-repair') REPO = 'tasksource/tasksource-jev-typed-decisions' PARENT = '94c2ebb18662a11f9d362f9f469aa13599e6f2dd' BASE = Path('build/vision-expanded-5000/dataset') ADD = Path('build/vision-append-release/additions/dataset') disable_progress_bars() def dump(path, value): path.write_text(json.dumps(value, indent=2, ensure_ascii=False) + '\n') def remote(name): return Path(hf_hub_download(REPO, name, repo_type='dataset', revision=PARENT)) def stage(): api = HfApi() info = api.dataset_info(REPO, files_metadata=True) assert info.sha == PARENT, 'Review new Hub parent before repairing' sizes = {f.rfilename: f.size for f in info.siblings} if BASE.exists() and ADD.exists(): original = load_from_disk(str(BASE)) additions = load_from_disk(str(ADD)) else: published = load_dataset(REPO, 'vision', revision=PARENT) base_counts = {'train': 60097, 'validation': 375, 'test': 175} original = DatasetDict({s: rows.select(range(base_counts[s])) for s, rows in published.items()}) additions = DatasetDict({s: rows.select(range(base_counts[s], len(rows))) for s, rows in published.items()}) train = original['train'] fields = ['state', 'metadata', 'license', 'license_use', 'id', 'group_id', 'question_id', 'example_id'] replacements = {key: [] for key in fields} prompt_counts, license_counts, duplicates = Counter(), Counter(), Counter() seen, kept = {}, [] evidence = {} for index, row in enumerate(train.select_columns([k for k in train.column_names if k != 'images'])): metadata = json.loads(row['metadata']) state = clean_cauldron_question(row['state']) if metadata.get('source_question') else row['state'] old_license = metadata['licenses'] new_license = source_license(row['source'], provenance_repos(metadata['provenance']), old_license.get('card_licenses', {})) # Only incorporate newly reviewed original-source evidence, retaining all # other source classifications exactly as published. if 'source_license_evidence' not in new_license: new_license = old_license evidence[row['source']] = new_license changed_state = state != row['state'] changed_license = new_license != old_license if changed_state or changed_license: metadata['export_repair'] = {'version': 1, 'parent_revision': PARENT, 'previous_id': row['id']} if changed_license: metadata['licenses'] = new_license row.update({key: new_license[key] for key in ('license', 'license_use')}) license_counts[row['source']] += 1 if changed_state: prompt_counts[row['source']] += 1 images = metadata['image_ids'] image_id = hashlib.sha256('\x1f'.join(images).encode()).hexdigest()[:24] row['state'] = state row['group_id'] = f"{row['source']}:train:{image_id}:{hashlib.sha256(state.encode()).hexdigest()[:16]}" decision = json.dumps([state, row['question'], row['options']], ensure_ascii=False) row['question_id'] = hashlib.sha256(decision.encode()).hexdigest()[:24] row['id'] = row['group_id'] + ':' + row['question_id'] row['example_id'] = hashlib.sha256(('\x1f'.join(images) + example_key( row['source'], state, row['options'], row['target'])).encode()).hexdigest()[:24] key = (row['source'], tuple(metadata['image_ids']), state, row['question'], tuple(row['options'])) if key in seen: assert row['target'] == seen[key], 'Conflicting native targets after cleanup' duplicates[row['source']] += 1 else: kept.append(index) seen[key] = row['target'] row['metadata'] = json.dumps(metadata, ensure_ascii=False, sort_keys=True) if changed_state or changed_license else row['metadata'] for field in fields: replacements[field].append(row[field]) table = train.data.table for field, values in replacements.items(): table = table.set_column(table.schema.get_field_index(field), table.schema.field(field), pa.array(values, type=table.schema.field(field).type)) fingerprint = hashlib.sha256((PARENT + Path(__file__).read_text()).encode()).hexdigest() patched = Dataset(table, info=copy.deepcopy(train.info), fingerprint=fingerprint).select(kept) validate_decisions(patched, 'train') assert len(set(patched['id'])) == len(patched) files = [] patched_bytes = 0 names = sorted(name for name in sizes if re.fullmatch(r'vision/train-\d{5}-of-\d{5}\.parquet', name)) assert len(names) == 36 and len(train) == 60097 for i, name in enumerate(names): part = patched.shard(len(names), i, contiguous=True) path = ROOT / Path(name).name part.to_parquet(path) # Compare serialized image payloads and gold decisions, with no image # decoding or re-encoding. Only explicit repair fields can change. expected = part.with_format('arrow')[:] patched_bytes += expected.nbytes restored = pq.read_table(path) for field in part.column_names: assert restored[field].equals(expected[field]), (name, field) files.append({'local': str(path), 'remote': name, 'bytes': path.stat().st_size, 'sha256': hashlib.sha256(path.read_bytes()).hexdigest()}) print(f"staged {i+1}/{len(names)} {path.name}", flush=True) release = json.loads(remote('vision/release-audit.json').read_text()) sources = yaml.safe_load(remote('vision/sources.yaml').read_text()) for source, license_info in evidence.items(): sources['sources'][source].update(license_info) report = {'parent_revision': PARENT, 'prompt_suffixes_removed': dict(prompt_counts), 'license_evidence_filled': dict(license_counts), 'identical_requests_deduplicated': dict(duplicates), 'truncated_answer_should_be_states': 0, 'checks': ['every written Parquet column round-tripped exactly', 'image bytes, ordering, options and gold targets preserved for retained rows', 'deduplicated requests have identical native targets', 'unique repaired decision IDs'], 'license_policy': {'allowed_uses': ['commercial', 'non-commercial', 'unspecified'], 'note': 'Mixed-license scope retained; unspecified is not permission.'}, 'splits': {}} for split in release['splits']: parts = [patched if split == 'train' else original[split], additions[split]] counts, families, uses = Counter(), Counter(), Counter() for part in parts: for row in part.select_columns(['source', 'license_use', 'state']): assert not row['state'].rstrip().endswith('Your answer should be') counts[row['source']] += 1 families['/'.join(row['source'].split('/')[:2])] += 1 uses[row['license_use']] += 1 summary = {'rows': sum(counts.values()), 'sources': dict(counts), 'families': dict(families), 'license_use': dict(uses)} release['splits'][split] = summary report['splits'][split] = {'rows': summary['rows'], 'license_use': dict(uses)} for source, count in counts.items(): sources['sources'][source]['rows'][split] = count release['repair'] = report dump(ROOT / 'release-audit.json', release) dump(ROOT / 'repair-audit.json', report) sources['parent_tasksource_commit'] = sources['tasksource_commit'] sources['tasksource_commit'] = subprocess.check_output(['git', 'rev-parse', 'HEAD'], text=True).strip() (ROOT / 'sources.yaml').write_text(yaml.safe_dump(sources, sort_keys=False)) manifest = {'operation': 'exact source-prompt cleanup and reviewed original-license evidence', 'parent_revision': PARENT, 'tasksource_commit': sources['tasksource_commit'], 'operation_script_sha256': hashlib.sha256(Path(__file__).read_bytes()).hexdigest(), 'license_policy': report['license_policy'], 'files': files, 'parent_manifest': json.loads(remote('vision/build-manifest.json').read_text())} dump(ROOT / 'build-manifest.json', manifest) quality = json.loads(remote('vision/quality-audit.json').read_text()) quality['repair_audit'] = report dump(ROOT / 'quality-audit.json', quality) card = DatasetCard.load(remote('README.md')) vision = next(entry for entry in card.data.dataset_info if entry['config_name'] == 'vision') stat = next(entry for entry in vision['splits'] if entry['name'] == 'train') stat['num_examples'] = release['splits']['train']['rows'] stat['num_bytes'] += patched_bytes - train.data.nbytes vision['dataset_size'] = sum(entry['num_bytes'] for entry in vision['splits']) vision['download_size'] += sum(f['bytes'] - sizes[f['remote']] for f in files) card.text = card.text.replace('66,097 train', '66,085 train') card.text += '''\n### Vision prompt and license correction (2026-10-09) Known Cauldron answer-style suffixes were removed from 18,353 training rows; complete original questions remain in metadata. Twelve identical MapQA requests with identical gold answers were deduplicated. Images and retained gold targets are unchanged. There are **66,085 train, 972 validation and 475 test** decisions. Original dataset terms for [CLEVR](https://cs.stanford.edu/people/jcjohns/clevr/), [MapQA](https://github.com/OSU-slatelab/MapQA/blob/main/license), and [TQA](https://registry.opendata.aws/allenai-tqa/) fill missing Hub-card evidence. Training license-use counts are **26,987 commercial, 7,000 non-commercial, and 32,098 unspecified**. This remains a **mixed-license research pilot**, not a commercial-cleared dataset. Unspecified does not grant permission. NLVR2 photo rights and other unresolved sources remain unresolved; repository software licenses do not establish image rights. LVIS/COCO classification conservatively reflects the NC images included in their source mirrors. Filter `license_use` when loading; new Tasksource vision builds also accept `--license-use commercial` to exclude unresolved/NC sources before loading them. See [repair-audit.json](vision/repair-audit.json) and the reproducible [repair script](vision/repair.py); both record the pinned parent release. ''' card.save(ROOT / 'README.md') dump(ROOT / 'staged.json', {'parent': PARENT, 'files': files}) print(json.dumps(report, indent=2), flush=True) def publish(): api = HfApi() staged = json.loads((ROOT / 'staged.json').read_text()) assert api.dataset_info(REPO).sha == PARENT, 'Hub changed since staging' operations = [CommitOperationAdd(path_in_repo=f['remote'], path_or_fileobj=f['local']) for f in staged['files']] for name in ('release-audit.json', 'repair-audit.json', 'sources.yaml', 'build-manifest.json', 'quality-audit.json', 'repair.py'): operations.append(CommitOperationAdd(path_in_repo='vision/' + name, path_or_fileobj=str(ROOT / name))) operations.append(CommitOperationAdd(path_in_repo='README.md', path_or_fileobj=str(ROOT / 'README.md'))) result = api.create_commit(REPO, repo_type='dataset', parent_commit=PARENT, operations=operations, commit_message='Clean vision prompt artifacts and fill original dataset license evidence') dump(ROOT / 'published.json', {'revision': result.oid, 'url': result.commit_url}) print(result.commit_url, flush=True) if __name__ == '__main__': publish() if '--publish' in sys.argv else stage()