Datasets:
Formats:
csv
Languages:
English
Size:
1K - 10K
Tags:
arxiv-artifact
reproducibility
research-artifact
computer-science
computer-logic
formal-methods
License:
| from __future__ import annotations | |
| import argparse | |
| import csv | |
| import json | |
| import re | |
| from datetime import datetime | |
| from pathlib import Path | |
| ROOT = Path(__file__).resolve().parents[1] | |
| PAPER = ROOT / "arxiv" / "paper.tex" | |
| def main() -> int: | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--detector", default="runs/remote_gpu/benchmark-detector-gpu/traces.csv") | |
| parser.add_argument("--detector-metrics", default="runs/remote_gpu/benchmark-detector-gpu/metrics.json") | |
| parser.add_argument("--sweep", default="runs/remote_gpu/sweep-detector-gpu/sweep_traces.csv") | |
| parser.add_argument("--metrics", default="runs/remote_gpu/sweep-detector-gpu/sweep_metrics.json") | |
| parser.add_argument("--telemetry-dir", default="runs/remote_gpu") | |
| args = parser.parse_args() | |
| detector = _best_trace(ROOT / args.detector, telemetry_dir=ROOT / args.telemetry_dir, trace_name="traces.csv", metrics_name="metrics.json") | |
| detector_metrics = detector.parent / "metrics.json" if detector is not None else ROOT / args.detector_metrics | |
| sweep = _best_trace(ROOT / args.sweep, telemetry_dir=ROOT / args.telemetry_dir, trace_name="sweep_traces.csv", metrics_name="sweep_metrics.json") | |
| metrics = sweep.parent / "sweep_metrics.json" if sweep is not None else ROOT / args.metrics | |
| telemetry_dir = ROOT / args.telemetry_dir | |
| updates: dict[str, str] = {} | |
| if detector and detector.exists(): | |
| detector_rows, detector_clips = count_trace(detector) | |
| updates["DetectorRows"] = str(detector_rows) | |
| updates["DetectorClips"] = str(detector_clips) | |
| if detector_metrics.exists(): | |
| data = json.loads(detector_metrics.read_text()) | |
| elapsed = float(data.get("elapsed_seconds", 0.0)) | |
| rows = int(data.get("rows", updates.get("DetectorRows", 0))) | |
| if elapsed > 0 and rows > 0: | |
| updates["DetectorThroughput"] = f"{rows / elapsed:.1f}" | |
| if sweep and sweep.exists(): | |
| sweep_rows, _ = count_trace(sweep) | |
| updates["SweepRows"] = str(sweep_rows) | |
| if metrics.exists(): | |
| data = json.loads(metrics.read_text()) | |
| updates["SweepFalsePositive"] = f"{float(data.get('false_positive_mean', 0.0)):.3f}" | |
| updates["SweepLocalization"] = f"{float(data.get('localization_error_mean', 0.0)):.2f}" | |
| updates["SweepStability"] = f"{float(data.get('certificate_stability', 0.0)):.2f}" | |
| if "rows" in data: | |
| updates["SweepRows"] = str(int(data["rows"])) | |
| if "clips" in data and "DetectorClips" not in updates: | |
| updates["DetectorClips"] = str(int(data["clips"])) | |
| telemetry = telemetry_summary(telemetry_dir) | |
| if telemetry: | |
| peak = telemetry["peak_util"] | |
| current_peak = current_macro_int(PAPER, "GpuPeak") | |
| if current_peak is not None: | |
| peak = max(peak, current_peak) | |
| updates["GpuPeak"] = str(int(round(peak))) | |
| updates["GpuMean"] = str(int(round(telemetry["mean_util"]))) | |
| updates["GpuHours"] = f"{telemetry['hours']:.2f}" | |
| updates["GpuVramPeak"] = f"{telemetry['peak_mem_mib'] / 1024.0:.1f}" | |
| if not updates: | |
| raise SystemExit("No metric inputs found; manuscript was not changed.") | |
| rewrite_macros(PAPER, updates) | |
| print(json.dumps(updates, indent=2, sort_keys=True)) | |
| return 0 | |
| def count_trace(path: Path) -> tuple[int, int]: | |
| with path.open(newline="") as f: | |
| reader = csv.DictReader(f) | |
| rows = 0 | |
| videos: set[str] = set() | |
| for row in reader: | |
| rows += 1 | |
| if row.get("video_id"): | |
| videos.add(row["video_id"]) | |
| return rows, len(videos) | |
| def _best_trace(default: Path, telemetry_dir: Path, trace_name: str, metrics_name: str) -> Path | None: | |
| candidates: list[Path] = [] | |
| if default.exists(): | |
| candidates.append(default) | |
| if telemetry_dir.exists(): | |
| candidates.extend(path for path in telemetry_dir.glob(f"**/{trace_name}") if (path.parent / metrics_name).exists()) | |
| if not candidates: | |
| return None | |
| return max(candidates, key=lambda path: count_trace(path)[0]) | |
| def telemetry_summary(root: Path) -> dict[str, float] | None: | |
| utils: list[int] = [] | |
| mems: list[int] = [] | |
| times: list[datetime] = [] | |
| for path in root.glob("**/gpu_telemetry*.csv"): | |
| with path.open(newline="") as f: | |
| for row in csv.reader(f): | |
| if row and row[0].strip().lower() == "timestamp": | |
| continue | |
| timestamp = parse_timestamp(row[0]) if row else None | |
| if timestamp is not None: | |
| times.append(timestamp) | |
| row_mem = None | |
| for cell in row: | |
| match = re.search(r"(\d+)\s*%", cell) | |
| if match: | |
| utils.append(int(match.group(1))) | |
| mem_match = re.search(r"(\d+)\s*MiB", cell) | |
| if mem_match and row_mem is None: | |
| row_mem = int(mem_match.group(1)) | |
| if row_mem is not None: | |
| mems.append(row_mem) | |
| if not utils: | |
| return None | |
| hours = 0.0 | |
| if len(times) >= 2: | |
| hours = max(0.0, (max(times) - min(times)).total_seconds() / 3600.0) | |
| return { | |
| "peak_util": float(max(utils)), | |
| "mean_util": float(sum(utils) / len(utils)), | |
| "peak_mem_mib": float(max(mems) if mems else 0), | |
| "hours": hours, | |
| } | |
| def parse_timestamp(value: str) -> datetime | None: | |
| value = value.strip() | |
| for fmt in ("%Y/%m/%d %H:%M:%S.%f", "%Y/%m/%d %H:%M:%S"): | |
| try: | |
| return datetime.strptime(value, fmt) | |
| except ValueError: | |
| pass | |
| return None | |
| def current_macro_int(path: Path, name: str) -> int | None: | |
| match = re.search(rf"\\newcommand{{\\{name}}}{{(\d+)}}", path.read_text()) | |
| return int(match.group(1)) if match else None | |
| def rewrite_macros(path: Path, updates: dict[str, str]) -> None: | |
| text = path.read_text() | |
| for name, value in updates.items(): | |
| text, count = re.subn( | |
| rf"\\newcommand{{\\{name}}}{{[^}}]*}}", | |
| rf"\\newcommand{{\\{name}}}{{{value}}}", | |
| text, | |
| count=1, | |
| ) | |
| if count == 0: | |
| raise SystemExit(f"Macro not found: {name}") | |
| path.write_text(text) | |
| if __name__ == "__main__": | |
| raise SystemExit(main()) | |