sindoring
aa799a2c7d
Синхронизация с upstream до e2aeaecf: исправления AccessKit на Windows, прокрутки трекпада на Linux и анимации моделей в меню.
MoonWell: расчёт рассеяния, вторичного освещения и AO перенесён в половинное разрешение с восстановлением по глубине. В контрольной сцене RTX 5070 суммарное время постобработки снизилось с 6,41 до 3,47 мс. При выключенном расширении изображение совпадает с исходным. Добавлен анализатор диагностических логов GPU.
Исправлена подготовка тестов интерфейса и обработка отсутствующих кинороликов в сокращённой установке. Уточнены причины существующих отклонений русского пакета и HD-атласа.
Проверки: 46 тестов графического модуля и сравнения дневных/ночных кадров пройдены; полный цикл scripts/gates.sh пройден: fmt, Clippy workspace и player, reference, тесты с установкой и без неё, документация, каталог сообщений, проверка GPU-проходов и запуск движка с данными и без. Проверки отсутствующих аддонов и четырёх кинороликов явно пропущены. Живой вход/выход на сервер не выполнялся.
113 lines
4.3 KiB
Python
113 lines
4.3 KiB
Python
#!/usr/bin/env python3
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"""Summarize GPU readback means by session and settings epoch, without mixing toggles.
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Usage: python scripts/analyze-gfx-diagnostics.py Diagnostics [another/Diagnostics]
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Pass times are weighted by readback frames, not by wall-clock seconds. CPU schedule
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phases overlap worker/render work and must not be summed into a frame time.
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"""
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import argparse
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import collections
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import csv
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import json
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import re
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from pathlib import Path
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def percentile(values, fraction):
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values = sorted(values)
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return values[int((len(values) - 1) * fraction)] if values else None
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def summarize(root):
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text = (root / "gpu-passes.log").read_text(encoding="utf-8-sig")
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epochs = []
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current = {}
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for line in text.splitlines():
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session = re.search(r"session=(\S+)", line)
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if not session:
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continue
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session = session[1]
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if " tag mwgfx=" in line:
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settings = dict(re.findall(r"([\w.]+)=([^\s]+)", line.split("tag mwgfx=", 1)[1]))
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epoch = {"session": session, "settings": settings, "samples": []}
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current[session] = epoch
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epochs.append(epoch)
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if " GPU_PASSES " not in line:
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continue
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pairs = dict(re.findall(r"(\w+)=([\d.]+)", line.split("GPU_PASSES", 1)[1]))
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frames = int(pairs.pop("frames", 0))
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if frames <= 0:
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continue
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if session not in current:
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current[session] = {"session": session, "settings": {}, "samples": []}
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epochs.append(current[session])
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current[session]["samples"].append((frames, {k: float(v) for k, v in pairs.items()}))
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result = {"source": str(root), "adapters": sorted(set(re.findall(
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r"# benilla fps journal[^\n]+", text))), "epochs": []}
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for epoch in epochs:
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samples = epoch.pop("samples")
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if not samples:
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continue
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n = sum(w for w, _ in samples)
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totals = collections.defaultdict(float)
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for weight, passes in samples:
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for name, ms in passes.items():
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totals[name] += weight * ms
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mean = {k: v / n for k, v in totals.items()}
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epoch.update(readbacks=len(samples), frames=n,
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mean_ms=dict(sorted(mean.items(), key=lambda item: -item[1])),
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total_measured_ms=sum(mean.values()))
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result["epochs"].append(epoch)
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# CSV may contain repeated headers and adapter banners from multiple launches.
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header = None
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fps = collections.defaultdict(list)
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path = root / "fps-journal.csv"
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if path.exists():
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for line in path.read_text(encoding="utf-8-sig").splitlines():
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if not line or line.startswith("#"):
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continue
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row = next(csv.reader([line]))
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if row[0] == "t":
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header = row
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continue
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if header is None:
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continue
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for key, value in zip(header, row):
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if key not in ("mean_ms", "main_ms", "gpu_ms", "p95_ms"):
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continue
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try:
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fps[key].append(float(value))
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except ValueError:
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pass
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result["journal_ms"] = {key: {"samples": len(values),
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"median": percentile(values, .5), "p95": percentile(values, .95)}
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for key, values in fps.items()}
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phases = collections.defaultdict(list)
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path = root / "cpu-phases.csv"
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if path.exists():
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lines = (line for line in path.read_text(encoding="utf-8-sig").splitlines()
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if line and not line.startswith("#"))
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for row in csv.DictReader(lines):
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try:
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phases[row["phase"]].append(float(row["wall_ms"]))
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except (ValueError, KeyError, TypeError):
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pass
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result["cpu_phase_wall_ms"] = {key: {"median": percentile(values, .5),
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"p95": percentile(values, .95)} for key, values in phases.items()}
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return result
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("folders", nargs="+", type=Path)
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parser.add_argument("--output", type=Path, help="Write a UTF-8 JSON report")
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args = parser.parse_args()
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report = json.dumps([summarize(root) for root in args.folders], indent=2)
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if args.output:
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args.output.write_text(report + "\n", encoding="utf-8")
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else:
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print(report)
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