| |
| """Generate markdown comparison report from hparam sweep CSV.""" |
|
|
| import argparse |
| import csv |
| from datetime import datetime |
| from pathlib import Path |
|
|
|
|
| def score_row(r): |
| try: |
| psnr = float(r["psnr_db"]) |
| if psnr == float("inf"): |
| psnr = 100.0 |
| reuse = float(r["reuse_rate_pct"] or 0) |
| wall = float(r["wall_sec"] or 99999) |
| |
| return psnr + 0.015 * reuse - 0.0001 * wall |
| except (ValueError, TypeError): |
| return -9999 |
|
|
|
|
| def fmt_psnr(v): |
| try: |
| f = float(v) |
| if f > 50: |
| return "∞" |
| return f"{f:.2f} dB" |
| except (ValueError, TypeError): |
| return "N/A" |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--results", required=True) |
| parser.add_argument("--baseline", required=True) |
| parser.add_argument("--output", required=True) |
| parser.add_argument("--sweep_dir", default="") |
| args = parser.parse_args() |
|
|
| rows = list(csv.DictReader(open(args.results))) |
| dev3 = [r for r in rows if r["version"] == "dev3" and r["psnr_db"] not in ("NA", "")] |
| dev4 = [r for r in rows if r["version"] == "dev4" and r["psnr_db"] not in ("NA", "")] |
| dev3_full = [r for r in rows if r["version"] == "dev3_full" and r["psnr_db"] not in ("NA", "")] |
| dev4_full = [r for r in rows if r["version"] == "dev4_full" and r["psnr_db"] not in ("NA", "")] |
|
|
| best_dev3 = max(dev3, key=score_row) if dev3 else None |
| best_dev4 = max(dev4, key=score_row) if dev4 else None |
|
|
| lines = [ |
| "# MotionCache (dev3) vs MotionDetailCache (dev4) 超参对比报告", |
| "", |
| f"生成时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}", |
| "", |
| f"Baseline：`{args.baseline}`（FlowCache 全量推理）", |
| f"Sweep 目录：`{args.sweep_dir}`", |
| "", |
| "## 评分方法", |
| "", |
| "综合得分 = PSNR + 0.015 × reuse_rate(%) − 0.0001 × wall_time(s)", |
| "（画质优先，适度奖励更高 reuse、更短耗时）", |
| "", |
| ] |
|
|
| if best_dev3: |
| lines += [ |
| "## dev3 最优超参（120 帧 sweep）", |
| "", |
| f"| 参数 | 值 |", |
| f"|------|-----|", |
| f"| rel_l1_thresh (τ) | **{best_dev3['tau']}** |", |
| f"| alpha | {best_dev3['alpha']} |", |
| f"| PSNR | {fmt_psnr(best_dev3['psnr_db'])} |", |
| f"| SSIM | {best_dev3['ssim']} |", |
| f"| reuse_rate | {best_dev3['reuse_rate_pct']}% |", |
| f"| 耗时 | {best_dev3['wall_sec']}s |", |
| f"| variant | `{best_dev3['variant']}` |", |
| "", |
| ] |
|
|
| if best_dev4: |
| lines += [ |
| "## dev4 最优超参（120 帧 sweep，τ 固定为 dev3 最优）", |
| "", |
| f"| 参数 | 值 |", |
| f"|------|-----|", |
| f"| rel_l1_thresh (τ) | {best_dev4['tau']} |", |
| f"| detail_alpha | **{best_dev4['detail_alpha']}** |", |
| f"| detail_window_size | **{best_dev4['detail_window']}** |", |
| f"| weight_combine_mode | **{best_dev4['combine_mode']}** |", |
| f"| detail_lambda | {best_dev4['detail_lambda']} |", |
| f"| PSNR | {fmt_psnr(best_dev4['psnr_db'])} |", |
| f"| SSIM | {best_dev4['ssim']} |", |
| f"| reuse_rate | {best_dev4['reuse_rate_pct']}% |", |
| f"| 耗时 | {best_dev4['wall_sec']}s |", |
| f"| variant | `{best_dev4['variant']}` |", |
| "", |
| ] |
|
|
| lines += ["## dev3 全量 τ sweep 结果", "", "| τ | PSNR | reuse% | 耗时(s) | 得分 |", "|---|------|--------|---------|------|"] |
| for r in sorted(dev3, key=lambda x: float(x["tau"])): |
| lines.append( |
| f"| {r['tau']} | {fmt_psnr(r['psnr_db'])} | {r['reuse_rate_pct']} | {r['wall_sec']} | {score_row(r):.3f} |" |
| ) |
| lines.append("") |
|
|
| lines += ["## dev4 全量 detail sweep 结果", "", "| mode | win | d_α | λ | PSNR | reuse% | 耗时(s) | 得分 |", "|------|-----|-----|---|------|--------|---------|------|"] |
| for r in sorted(dev4, key=score_row, reverse=True): |
| lines.append( |
| f"| {r['combine_mode']} | {r['detail_window']} | {r['detail_alpha']} | {r['detail_lambda']} " |
| f"| {fmt_psnr(r['psnr_db'])} | {r['reuse_rate_pct']} | {r['wall_sec']} | {score_row(r):.3f} |" |
| ) |
| lines.append("") |
|
|
| if dev3_full or dev4_full: |
| lines += ["## 240 帧全分辨率验证", "", "| 版本 | PSNR | reuse% | 耗时(s) |", "|------|------|--------|---------|"] |
| for r in dev3_full + dev4_full: |
| lines.append(f"| {r['version']} ({r['variant']}) | {fmt_psnr(r['psnr_db'])} | {r['reuse_rate_pct']} | {r['wall_sec']} |") |
| lines.append("") |
|
|
| if best_dev3 and best_dev4: |
| d3p = float(best_dev3["psnr_db"]) if best_dev3["psnr_db"] != "inf" else 100 |
| d4p = float(best_dev4["psnr_db"]) if best_dev4["psnr_db"] != "inf" else 100 |
| d3r = float(best_dev3["reuse_rate_pct"] or 0) |
| d4r = float(best_dev4["reuse_rate_pct"] or 0) |
| d3t = float(best_dev3["wall_sec"]) |
| d4t = float(best_dev4["wall_sec"]) |
| lines += [ |
| "## 结论摘要", |
| "", |
| f"- **dev3 推荐配置**：τ={best_dev3['tau']}，PSNR {fmt_psnr(best_dev3['psnr_db'])}，reuse {d3r:.1f}%", |
| f"- **dev4 推荐配置**：mode={best_dev4['combine_mode']}, window={best_dev4['detail_window']}, " |
| f"detail_α={best_dev4['detail_alpha']}, λ={best_dev4['detail_lambda']}，" |
| f"PSNR {fmt_psnr(best_dev4['psnr_db'])}，reuse {d4r:.1f}%", |
| f"- dev4 vs dev3 PSNR 差：{d4p - d3p:+.2f} dB；reuse 差：{d4r - d3r:+.1f}%；耗时差：{d4t - d3t:+.0f}s", |
| "", |
| "### 推荐 yaml 片段", |
| "", |
| "**dev3** (`motioncache_config.yaml`):", |
| "```yaml", |
| f"rel_l1_thresh: {best_dev3['tau']}", |
| "alpha: 0.5", |
| "phase1_steps: 9", |
| "warmup_steps: 5", |
| "```", |
| "", |
| "**dev4** (`motiondetail_config.yaml`):", |
| "```yaml", |
| f"rel_l1_thresh: {best_dev4['tau']}", |
| f"detail_alpha: {best_dev4['detail_alpha']}", |
| f"detail_window_size: {int(float(best_dev4['detail_window']))}", |
| f"weight_combine_mode: {best_dev4['combine_mode']}", |
| f"detail_lambda: {best_dev4['detail_lambda']}", |
| "alpha: 0.5", |
| "phase1_steps: 9", |
| "warmup_steps: 5", |
| "```", |
| ] |
|
|
| Path(args.output).write_text("\n".join(lines) + "\n", encoding="utf-8") |
| print(f"Report written to {args.output}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
