Datasets:
File size: 3,935 Bytes
642a47b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | """Rebuild Endless v3 tasks.parquet and archive.parquet from pinned v2 Parquets and metadata/selection.json.
pip install pyarrow huggingface_hub
python patch.py --out rebuilt
Optional --source-dir holds v2 tasks.parquet and archive.parquet for offline reproduction.
"""
import argparse, json
from pathlib import Path
import pyarrow as pa
import pyarrow.parquet as pq
def build(out, source_dir=None):
m = json.loads((Path(__file__).parent / 'metadata/selection.json').read_text())
def source(name):
if source_dir:
return source_dir / name
from huggingface_hub import hf_hub_download
return Path(hf_hub_download(m['repo_id'], f'endless_v2/{name}', repo_type='dataset',
revision=m['v2_revision'], cache_dir=out / '.source-cache'))
out.mkdir(parents=True, exist_ok=True)
assert not any((out / n).exists() for n in ['tasks.parquet', 'archive.parquet'])
old, arch = pq.read_table(source('tasks.parquet')), pq.read_table(source('archive.parquet'))
extra = [pa.field('qwen38_attempts', pa.int64()), pa.field('qwen38_successes', pa.int64()),
pa.field('qwen38_target_attempts', pa.int64()), pa.field('kept_from_v2', pa.bool_())]
kept, excluded = [], []
for r in old.to_pylist():
assert m['tasks'][r['path']]['kept_from_v2']
kept.append({**r, 'qwen38_attempts': 0, 'qwen38_successes': None, 'qwen38_target_attempts': None, 'kept_from_v2': True})
for r in arch.to_pylist():
e = m['tasks'][r['path']]
assert r['content_sha256'] == e['qwen38_evaluated_content_sha256']
r.update(qwen38_attempts=e['qwen38_attempts'], qwen38_successes=e['qwen38_successes'],
qwen38_target_attempts=m['attempts'], kept_from_v2=False)
if e['kept']:
r.update(archive_stage=None, archive_reason=None, archive_labels=[])
kept.append(r)
else:
r.update(archive_reason='zero_success_three_models', archive_labels=['zero_success_three_models'])
excluded.append(r)
def images(rows):
merged = json.loads(old.schema.metadata[b'ot.images.v1'])
other = json.loads(arch.schema.metadata[b'ot.images.v1'])
merged['tasks'].update(other['tasks'])
merged['bundles'].update(other['bundles'])
names = {r['path'] for r in rows}
merged['tasks'] = {t: e for t, e in merged['tasks'].items() if t in names}
used = {e['bundle'] for t in merged['tasks'].values() for e in t['environments']}
merged['bundles'] = {k: v for k, v in merged['bundles'].items() if k in used}
if 'uncached_task_ids' in merged:
merged['uncached_task_ids'] = sorted(names - set(merged['tasks']))
merged['coverage'] = {'cached_tasks': len(merged['tasks']), 'total_tasks': len(names)}
return json.dumps(merged).encode()
s = m['summary']
release = json.dumps({k: s[k] for k in ['previous_revision', 'source_folder', 'source_revision', 'new_model', 'attempts',
'evaluated', 'v2_kept', 'newly_solved', 'kept', 'reward_policy']}).encode()
for name, table, rows in [('tasks.parquet', old, kept), ('archive.parquet', arch, excluded)]:
schema = pa.schema([*table.schema, *extra])
pq.write_table(pa.Table.from_pylist(sorted(rows, key=lambda r: r['path']), schema=schema)
.replace_schema_metadata({b'ot.images.v1': images(rows), b'ot.release.v3': release}),
out / name, compression='zstd')
assert len(kept) == s['kept'] and len(excluded) == s['excluded']
print(json.dumps({'kept': len(kept), 'excluded': len(excluded)}))
if __name__ == '__main__':
p = argparse.ArgumentParser(description=__doc__)
p.add_argument('--out', type=Path, required=True)
p.add_argument('--source-dir', type=Path)
a = p.parse_args()
build(a.out, a.source_dir)
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