Datasets:
Download endless_v2/patch.py from FWeindel/validated-tasks: direct link, hf CLI and curl.
- Browser
- Download file 2.18 kB
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https://huggingface.co/datasets/FWeindel/validated-tasks/resolve/refs%2Fpr%2F23/endless_v2/patch.py
- Command line
-
hf download hf://datasets/FWeindel/validated-tasks@refs/pr/23/endless_v2/patch.py
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curl -L -o patch.py https://huggingface.co/datasets/FWeindel/validated-tasks/resolve/refs%2Fpr%2F23/endless_v2/patch.py
2.18 kB
| """Reproduce the frozen v2 selection from the unchanged, pinned v1 payloads.""" | |
| import argparse,json,hashlib | |
| from pathlib import Path | |
| import pyarrow as pa,pyarrow.parquet as pq | |
| from huggingface_hub import hf_hub_download | |
| p=argparse.ArgumentParser(description=__doc__);p.add_argument('--out',type=Path,required=True);p.add_argument('--source',type=Path);a=p.parse_args();a.out.mkdir(parents=True,exist_ok=True) | |
| assert not (a.out/'tasks.parquet').exists() | |
| m=json.loads((Path(__file__).parent/'metadata/selection.json').read_text());f=a.source or Path(hf_hub_download(m['repo_id'],m['source_folder']+'/tasks.parquet',revision=m['source_revision'],repo_type='dataset',cache_dir=a.out/'.source-cache'));assert hashlib.sha256(f.read_bytes()).hexdigest()==m['source_sha256'] | |
| src=pq.ParquetFile(f);schema=src.schema_arrow.remove_metadata();columns=[model+'_'+metric for model in m['models'] for metric in ['successes','graded_attempts','missing_attempts']] | |
| for name in columns+['target_attempts_per_model']:schema=schema.append(pa.field(name,pa.int64())) | |
| rows=[] | |
| for batch in src.iter_batches(batch_size=32): | |
| for r in batch.to_pylist(): | |
| t=m['tasks'][r['path']];assert r['content_sha256']==t['content_sha256'] | |
| if not t['kept']:continue | |
| for k in columns:r[k]=t[k] | |
| r['target_attempts_per_model']=4;rows.append(r) | |
| assert len(rows)==m['summary']['solved'];names={r['path'] for r in rows};im=json.loads(src.schema_arrow.metadata[b'ot.images.v1']);im['tasks']={k:v for k,v in im['tasks'].items() if k in names};bundles={e['bundle'] for v in im['tasks'].values() for e in v['environments']};im['bundles']={k:v for k,v in im['bundles'].items() if k in bundles} | |
| if 'uncached_task_ids' in im:im['uncached_task_ids']=sorted(names-set(im['tasks']));im['coverage']={'cached_tasks':len(im['tasks']),'total_tasks':len(names)} | |
| else:assert set(im['tasks'])==names | |
| meta={b'ot.images.v1':json.dumps(im).encode(),b'ot.release.v2':json.dumps({k:v for k,v in m.items() if k!='tasks'}).encode()};pq.write_table(pa.Table.from_pylist(rows,schema=schema).replace_schema_metadata(meta),a.out/'tasks.parquet',compression='zstd');print('Retained',len(rows),'cached tasks',len(im['tasks']),'bundles',len(bundles)) | |