Datasets:
File size: 1,612 Bytes
7e6690d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | """Reproduce tasks.parquet from the pinned v1 source and saved success selection."""
import argparse,json
from pathlib import Path
import pyarrow as pa
import pyarrow.parquet as pq
from huggingface_hub import hf_hub_download
def main():
p=argparse.ArgumentParser(description=__doc__);p.add_argument('--out',type=Path,default=Path('tasks.parquet'));a=p.parse_args()
selection=json.loads((Path(__file__).parent/'metadata/selection.json').read_text())
source=hf_hub_download('FWeindel/validated-tasks','nl2bash_v1/tasks.parquet',repo_type='dataset',revision=selection['base_revision'])
table=pq.read_table(source);rows=[]
for r in table.to_pylist():
s=selection['tasks'][r['path']];assert r['content_sha256']==s['content_sha256']
if s['kept']:
r.update(coder_successes=s['coder_successes'],coder_attempts=4,coder_graded_attempts=sum(v is not None for v in s['attempts'].values()));rows.append(r)
meta=dict(table.schema.metadata);images=json.loads(meta[b'ot.images.v1']);kept={r['path'] for r in rows};images['tasks']={k:v for k,v in images['tasks'].items() if k in kept};used={e['bundle'] for t in images['tasks'].values() for e in t['environments']};images['bundles']={k:v for k,v in images['bundles'].items() if k in used};meta[b'ot.images.v1']=json.dumps(images).encode()
schema=table.schema
for k in ['coder_successes','coder_attempts','coder_graded_attempts']:schema=schema.append(pa.field(k,pa.int64()))
pq.write_table(pa.Table.from_pylist(rows,schema=schema).replace_schema_metadata(meta),a.out,compression='zstd')
print(f'{len(rows)} kept tasks -> {a.out}')
if __name__=='__main__':main()
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