File size: 1,540 Bytes
2527e91 | 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 | from __future__ import annotations
import argparse
import json
from pathlib import Path
from datasets import load_dataset
def main() -> None:
parser = argparse.ArgumentParser(
description="Score RoutingBench Track A predictions."
)
parser.add_argument("predictions", type=Path)
parser.add_argument("--split", choices=("development", "validation", "test"))
parser.add_argument("--revision", default=None)
args = parser.parse_args()
rows = load_dataset(
"TrangBui/RoutingBench-V2",
"decision",
split=args.split,
revision=args.revision,
)
gold = {row["decision_id"]: set(row["admissible_actions"]) for row in rows}
predictions = {}
with args.predictions.open("r", encoding="utf-8") as handle:
for line in handle:
item = json.loads(line)
predictions[str(item["decision_id"])] = str(item["selected_action"])
missing = sorted(set(gold) - set(predictions))
unknown = sorted(set(predictions) - set(gold))
if missing or unknown:
raise SystemExit(
f"Prediction IDs mismatch: missing={len(missing)}, unknown={len(unknown)}"
)
correct = sum(predictions[key] in actions for key, actions in gold.items())
print(
json.dumps(
{
"split": args.split,
"count": len(gold),
"admissible_next_action_accuracy": correct / len(gold),
},
indent=2,
)
)
if __name__ == "__main__":
main()
|