Datasets:
Tasks:
Other
Formats:
parquet
Languages:
English
Size:
1K - 10K
Tags:
machine-learning
active-learning
representation-learning
sparse-fourier-transform
experimental-design
synthetic-data
| """Validate the prepared dataset locally; never authenticates or uploads.""" | |
| from pathlib import Path | |
| import json,os,hashlib | |
| os.environ['HF_HUB_OFFLINE']='1' | |
| os.environ['HF_DATASETS_OFFLINE']='1' | |
| import pyarrow.parquet as pq | |
| import yaml,datasets,huggingface_hub | |
| from huggingface_hub import DatasetCard | |
| ROOT=Path(__file__).resolve().parents[1] | |
| def main(): | |
| front=ROOT.joinpath('README.md').read_text(encoding='utf-8').split('---',2)[1] | |
| meta=yaml.safe_load(front) | |
| assert len(meta['configs'])==8 | |
| assert sum(bool(c.get('default'))for c in meta['configs'])==1 | |
| assert meta['configs'][0]['config_name']=='evaluation' | |
| assert 'license'not in meta | |
| card=DatasetCard.load(str(ROOT/'README.md')) | |
| assert len(card.data.to_dict()['configs'])==8 | |
| source={};records=[];contexts=[];row_counts={} | |
| for p in sorted((ROOT/'data').glob('*.parquet')): | |
| rows=pq.read_table(p).to_pylist() | |
| mirrors=[json.loads(l)for l in (ROOT/'tables_jsonl'/f'{p.stem}.jsonl').read_text().splitlines()] | |
| assert rows==mirrors | |
| row_counts[p.stem]=len(rows) | |
| if p.stem=='contexts':contexts=rows | |
| else:records.extend(rows) | |
| context_map={r['context_id']:r for r in contexts} | |
| assert len(context_map)==74 | |
| total_masks=0;large_masks=0 | |
| for r in records: | |
| f=r['source_file'] | |
| if f not in source:source[f]=json.loads((ROOT/f).read_text()) | |
| obj=source[f] | |
| for token in r['source_pointer'].split('/')[1:]: | |
| token=token.replace('~1','/').replace('~0','~') | |
| obj=obj[int(token)]if isinstance(obj,list)else obj[token] | |
| truth=obj['truth_evaluation'] | |
| assert r['oracle_calls']==obj['total_oracle_calls'] | |
| assert r['component_mse']==truth['component_mse'] | |
| assert r['certified']==truth['certified'] | |
| assert r['false_certificate_evaluation_only']==truth['false_certificate_evaluation_only'] | |
| assert r['oracle_calls']==r['specialized_readout_calls']+r['fresh_risk_audit_calls']+r['search_and_screen_calls'] | |
| assert r['context_id']in context_map | |
| for c in json.loads(r['charged_to_context_ids_json']):assert c in context_map | |
| masks=r['model_support_masks'];coefs=r['model_coefficients'] | |
| assert len(masks)==len(coefs)==r['model_terms'] | |
| assert dict(zip(masks,coefs))==obj['model'] | |
| for mask in masks: | |
| assert isinstance(mask,str)and str(int(mask))==mask | |
| assert 0<=int(mask)<(1<<r['dimension']) | |
| large_masks+=int(int(mask)>2**64-1);total_masks+=1 | |
| evaluations=[r for r in records if r['phase']=='evaluation'] | |
| warmup=[r for r in records if r['phase']=='warmup'] | |
| assert len(evaluations)==668 and len(warmup)==41 | |
| assert len({r['record_id']for r in records})==709 | |
| assert len({r['teacher_case_id']for r in evaluations})==148 | |
| assert len({r['teacher_case_id']for r in warmup})==21 | |
| assert sum(r['certified']for r in evaluations)==661 | |
| for c in contexts: | |
| calls=sum(r['oracle_calls']for r in evaluations if r['context_id']==c['context_id']) | |
| assert c['evaluation_oracle_calls']==calls | |
| assert c['training_inclusive_calls']==calls+c['charged_training_calls'] | |
| expected={'evaluation':668,'core_evaluation':324,'probe_evaluation':120,'strong_evaluation':192, | |
| 'unified_evaluation':32,'warmup_usages':41,'all_risk_records':709,'contexts':74} | |
| loaded={} | |
| # Load the local repository using actual dataset-card configuration, not | |
| # an independently reconstructed list of files. | |
| for config in meta['configs']: | |
| name=config['config_name'] | |
| data=datasets.load_dataset(str(ROOT),name=name) | |
| assert len(data)==1 | |
| split=list(data)[0] | |
| assert data[split].num_rows==expected[name] | |
| loaded[name]={'split':split,'rows':data[split].num_rows,'columns':len(data[split].column_names)} | |
| default=datasets.load_dataset(str(ROOT)) | |
| assert default['evaluation'].num_rows==668 | |
| archive=ROOT/'release/Nhioryum_Phi_Research_Package.zip' | |
| sha=hashlib.sha256(archive.read_bytes()).hexdigest() | |
| assert sha=='925b1b7a917c5a16c25f1ade5a08c9622366cbe3b0e6da828a3e9fbfa7ca8e54' | |
| result={'local_card_metadata_valid':True,'actual_datasets_local_load':loaded, | |
| 'default_config_load_rows':668,'parquet_jsonl_exact_roundtrip':True, | |
| 'source_pointer_records_verified':len(records),'context_rows_verified':len(contexts), | |
| 'support_masks_verified':total_masks,'support_masks_above_uint64_preserved_as_strings':large_masks, | |
| 'original_archive_sha256':sha,'datasets_version':datasets.__version__, | |
| 'huggingface_hub_version':huggingface_hub.__version__, | |
| 'remote_upload_performed':False,'network_disabled_for_validation':True} | |
| print(json.dumps(result,indent=2)) | |
| if __name__=='__main__':main() | |