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https://github.com/RYDE-WORK/lnp_ml.git
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66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
"""汇总消融实验结果：对比 baseline / +moe / +llm / +moe+llm 的 nested CV 指标。
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读取每个 run 目录下的 summary.json（nested_cv 产出），输出对比表 CSV 并打印。
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用法：
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python scripts/summarize_ablation.py \
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--run baseline=models/nested_cv/baseline/<timestamp> \
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--run +moe=models/nested_cv/moe/<timestamp> \
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--run +llm=models/nested_cv/llm/<timestamp> \
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--run +moe+llm=models/nested_cv/both/<timestamp> \
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--out reports/ablation_summary.csv
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"""
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from __future__ import annotations
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import argparse
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import json
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from pathlib import Path
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import pandas as pd
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def load_summary_stats(run_dir: Path) -> dict:
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"""读取 run 目录的 summary.json，返回 summary_stats。"""
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summary_path = run_dir / "summary.json"
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if not summary_path.exists():
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raise FileNotFoundError(f"summary.json not found in {run_dir}")
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with open(summary_path) as f:
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return json.load(f).get("summary_stats", {})
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def main() -> None:
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parser = argparse.ArgumentParser(description="Summarize ablation nested-CV runs")
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parser.add_argument(
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"--run", action="append", default=[],
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help="LABEL=run_dir，可重复传入多个变体",
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)
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parser.add_argument("--out", type=str, default="reports/ablation_summary.csv")
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args = parser.parse_args()
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if not args.run:
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parser.error("至少需要一个 --run LABEL=run_dir")
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rows = []
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for spec in args.run:
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label, sep, run_dir = spec.partition("=")
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if not sep:
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parser.error(f"--run 需为 LABEL=run_dir 形式，收到: {spec}")
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stats = load_summary_stats(Path(run_dir))
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row = {"variant": label, "run_dir": run_dir}
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for task, metrics in stats.items():
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for metric_name, value in metrics.items():
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row[f"{task}.{metric_name}"] = value
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rows.append(row)
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df = pd.DataFrame(rows)
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out = Path(args.out)
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out.parent.mkdir(parents=True, exist_ok=True)
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df.to_csv(out, index=False)
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print(df.to_string(index=False))
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print(f"\nSaved ablation summary to {out}")
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if __name__ == "__main__":
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main() |