Datasets:
Clarify first-run evaluation workflow and add transport completeness check (v1.0.1)
c4543f4 verified Download check_run.py from KETI-NLP/KMME: direct link, hf CLI and curl.
- Browser
- Download file 1.91 kB
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https://huggingface.co/datasets/KETI-NLP/KMME/resolve/main/check_run.py
- Command line
-
hf download hf://datasets/KETI-NLP/KMME/check_run.py
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curl -L -o check_run.py https://huggingface.co/datasets/KETI-NLP/KMME/resolve/main/check_run.py
1.91 kB
| # SPDX-License-Identifier: Apache-2.0 | |
| """Check transport completeness; this is not answer parsing or scoring.""" | |
| import argparse,json | |
| from pathlib import Path | |
| from collections import Counter | |
| def rows(path): | |
| with path.open(encoding="utf-8-sig") as f: | |
| return [json.loads(line) for line in f if line.strip()] | |
| def main(): | |
| p=argparse.ArgumentParser(description=__doc__) | |
| p.add_argument("--input",type=Path,required=True) | |
| p.add_argument("--predictions",type=Path,required=True) | |
| p.add_argument("--limit",type=int) | |
| a=p.parse_args() | |
| if a.limit is not None and a.limit<1:p.error("--limit must be positive") | |
| inputs=rows(a.input) | |
| if a.limit is not None:inputs=inputs[:a.limit] | |
| outputs=rows(a.predictions) | |
| expected=[r["sample_id"] for r in inputs] | |
| actual=[r.get("sample_id") for r in outputs] | |
| duplicate_input=len(expected)-len(set(expected)) | |
| duplicate_output=sum(n-1 for n in Counter(actual).values() if n>1) | |
| missing=set(expected)-set(actual);unknown=set(actual)-set(expected) | |
| api_failed=sum(r.get("api_status")!="ok" for r in outputs) | |
| empty=sum(not isinstance(r.get("prediction"),str) or not r.get("prediction","").strip() for r in outputs) | |
| models={r.get("evaluated_model") for r in outputs if r.get("evaluated_model")} | |
| ok=bool(expected) and not any([duplicate_input,duplicate_output,missing,unknown,api_failed,empty,len(models)>1]) | |
| print(json.dumps({"transport_check":"passed" if ok else "failed","expected":len(expected),"received":len(actual),"missing":len(missing),"unknown":len(unknown),"duplicate_input":duplicate_input,"duplicate_output":duplicate_output,"api_failed":api_failed,"empty_predictions":empty,"mixed_models":len(models)>1,"answer_parsing_checked":False,"model_accuracy_measured":False},ensure_ascii=False)) | |
| raise SystemExit(0 if ok else 1) | |
| if __name__=="__main__":main() | |