| |
| """Generate or check fast-tokenizer references at the revisions in manifest.json. |
| |
| Adapted from apocryphx/swift-transformers PR #360; see README.md for attribution. |
| Only Python reference outputs are written; Swift output never becomes a golden. |
| """ |
| import argparse |
| import datetime |
| import hashlib |
| import json |
| from pathlib import Path |
|
|
| import tokenizers |
| import transformers |
| from transformers import AutoTokenizer |
|
|
| ROOT = Path(__file__).resolve().parent.parent |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument('--check', action='store_true', help='Compare reference entries without writing files') |
| parser.add_argument('--corpus', help='Generate only this corpus (default: all)') |
| args = parser.parse_args() |
| manifest = json.loads((ROOT / 'manifest.json').read_text(encoding='utf-8')) |
| assert manifest['schema_version'] == 1 |
| corpora = [c for c in manifest['corpora'] if args.corpus is None or c['id'] == args.corpus] |
| if not corpora: |
| parser.error('No matching corpus') |
| failed = False |
| for corpus in corpora: |
| input_bytes = (ROOT / corpus['inputs']).read_bytes() |
| inputs = json.loads(input_bytes) |
| assert inputs and len({i['id'] for i in inputs}) == len(inputs), 'Empty corpus or duplicate IDs' |
| for spec in corpus['baselines']: |
| model = spec['model_id'] |
| revision = spec['revision'] |
| assert len(revision) == 40 and all(c in '0123456789abcdef' for c in revision) |
| print(f'{corpus["id"]}: {model}@{revision}', flush=True) |
| tokenizer = AutoTokenizer.from_pretrained(model, revision=revision, use_fast=True) |
| assert tokenizer.is_fast, 'References must use the fast tokenizer' |
| entries = [] |
| for row in inputs: |
| ids = tokenizer(row['text'], add_special_tokens=True)['input_ids'] |
| entries.append({ |
| 'id': row['id'], |
| 'input_ids': ids, |
| 'tokens': tokenizer.convert_ids_to_tokens(ids), |
| 'decoded_with_special': tokenizer.decode(ids, skip_special_tokens=False), |
| 'decoded_skip_special': tokenizer.decode(ids, skip_special_tokens=True), |
| }) |
| path = ROOT / spec['path'] |
| if args.check: |
| previous = json.loads(path.read_text(encoding='utf-8'))['entries'] |
| matches = previous == entries |
| print(f' {len(entries)} entries: {"MATCH" if matches else "DIFFER"}', flush=True) |
| failed |= not matches |
| continue |
| payload = { |
| 'metadata': { |
| 'model_id': model, 'model_revision': revision, |
| 'transformers_version': transformers.__version__, |
| 'tokenizers_version': tokenizers.__version__, |
| 'generated_at': datetime.datetime.now(datetime.timezone.utc).replace(microsecond=0).isoformat(), |
| 'input_count': len(entries), |
| 'inputs_sha256': hashlib.sha256(input_bytes).hexdigest(), |
| 'add_special_tokens': True, |
| }, |
| 'entries': entries, |
| } |
| path.parent.mkdir(parents=True, exist_ok=True) |
| path.write_text(json.dumps(payload, ensure_ascii=False, indent=2) + '\n', encoding='utf-8') |
| raise SystemExit(1 if failed else 0) |
|
|
|
|
| if __name__ == '__main__': |
| main() |
|
|
