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"""Summarize dense retrieval baseline runs into a compact CSV table."""
import argparse
import csv
import json
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
from baselines.dense_retrieval import DENSE_RETRIEVER_CONFIGS
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--output_dir", default="outputs/dense_retrieval_baselines")
parser.add_argument("--csv_name", default="dense_summary.csv")
args = parser.parse_args()
output_dir = Path(args.output_dir)
rows = []
for summary_path in sorted(output_dir.glob("*_K*/summary.json")):
with summary_path.open() as f:
summary = json.load(f)
task = summary.get("task")
setting = summary.get("setting")
K = summary.get("K")
aggregate = summary.get("aggregate", {})
for method, metrics in aggregate.items():
config = DENSE_RETRIEVER_CONFIGS.get(method)
rows.append({
"task": task,
"setting": setting,
"K": K,
"method": method,
"model": config.model_name if config else "",
"retrieval_text": config.text_mode if config else "",
"year": config.citation_year if config else "",
"rougeL": metrics.get("rougeL"),
"meteor": metrics.get("meteor"),
"sfd_nolen": metrics.get("sfd_nolen"),
"avg_len": metrics.get("avg_len"),
})
csv_path = output_dir / args.csv_name
csv_path.parent.mkdir(parents=True, exist_ok=True)
fieldnames = [
"task", "setting", "K", "method", "model", "retrieval_text", "year",
"rougeL", "meteor", "sfd_nolen", "avg_len",
]
with csv_path.open("w", newline="") as f:
writer = csv.DictWriter(f, fieldnames=fieldnames)
writer.writeheader()
writer.writerows(rows)
print(f"Wrote {csv_path} ({len(rows)} rows)")
if __name__ == "__main__":
main()
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