Datasets:
Download scripts/validate_artifact.py from Salesforce/BehaviorBench: direct link, hf CLI and curl.
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- Download file 2.74 kB
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https://huggingface.co/datasets/Salesforce/BehaviorBench/resolve/main/scripts/validate_artifact.py
- Command line
-
hf download hf://datasets/Salesforce/BehaviorBench/scripts/validate_artifact.py
-
curl -L -o validate_artifact.py https://huggingface.co/datasets/Salesforce/BehaviorBench/resolve/main/scripts/validate_artifact.py
2.74 kB
| #!/usr/bin/env python3 | |
| """Local structural checks for the BehaviorBench NeurIPS artifact.""" | |
| import json, re, sys | |
| from pathlib import Path | |
| import pyarrow as pa | |
| import pyarrow.parquet as pq | |
| ROOT=Path(__file__).resolve().parents[1] | |
| errors=[] | |
| required=["README.md","DATASET_CARD.md","LICENSE","CHANGELOG.md","croissant.json","docs/RESPONSIBLE_AI.md"] | |
| for x in required: | |
| if not (ROOT/x).exists(): errors.append(f"missing {x}") | |
| try: meta=json.loads((ROOT/"croissant.json").read_text()) | |
| except Exception as e: errors.append(f"invalid croissant JSON: {e}"); meta={} | |
| rai=["rai:dataLimitations","rai:dataBiases","rai:personalSensitiveInformation","rai:dataUseCases","rai:dataSocialImpact","rai:hasSyntheticData","rai:dataCollection"] | |
| for k in rai: | |
| if k not in meta: errors.append(f"missing Croissant RAI field {k}") | |
| files={p.relative_to(ROOT).as_posix():p for top in (ROOT/"dataset",ROOT/"benchmark") for p in top.rglob("*.parquet") if "evaluation/sources" not in p.as_posix()} | |
| dists={x.get("@id"):x for x in meta.get("distribution",[])} | |
| records={x.get("name"):x for x in meta.get("recordSet",[])} | |
| for rel,p in files.items(): | |
| if rel not in dists: errors.append(f"no distribution for {rel}") | |
| if rel not in records: errors.append(f"no recordSet for {rel}") | |
| else: | |
| schema=pq.ParquetFile(p).schema_arrow | |
| actual=set(schema.names) | |
| described={x.get("name") for x in records[rel].get("field",[])} | |
| if not described.issubset(actual): | |
| errors.append(f"schema contains unknown fields for {rel}") | |
| omitted=actual-described | |
| for name in omitted: | |
| t=schema.field(name).type | |
| # Current mlcroissant record generation cannot reliably cast | |
| # nested Parquet structs, including list<struct<...>> columns. | |
| nested_struct = pa.types.is_struct(t) or ( | |
| (pa.types.is_list(t) or pa.types.is_large_list(t)) | |
| and pa.types.is_struct(t.value_type) | |
| ) | |
| if not nested_struct: | |
| errors.append(f"unexplained omitted field {name} for {rel}") | |
| for rel in dists: | |
| if rel not in files: errors.append(f"distribution path not found: {rel}") | |
| # Relative Markdown links. | |
| for p in [ROOT/"README.md",ROOT/"DATASET_CARD.md",*sorted((ROOT/"docs").glob("*.md"))]: | |
| for link in re.findall(r"\[[^]]+\]\(([^)]+)\)",p.read_text()): | |
| if "://" not in link and not link.startswith("#") and not (p.parent/link).resolve().exists(): | |
| errors.append(f"broken link {p.relative_to(ROOT)} -> {link}") | |
| if errors: | |
| print("FAIL") | |
| print("\n".join(f"- {x}" for x in errors));sys.exit(1) | |
| print(f"PASS: {len(files)} Parquet distributions/record sets; required RAI fields and local links present.") | |