1055c9162f
verify-stress.sh already hard-fails a ceiling free-VRAM margin below the sustained-agent guard (default 1024 MB), but a margin that *passes* the guard yet sits close to it can still OOM on a second run or server restart — the marginal-but-passing case @laurimyllari hit on his 4090 at 160K (8/8 PASS, then a second rebench OOMed). The report dropped the margin number entirely, so a PASS read as comfortable headroom. parse_verify_stress now extracts the deepest-rung free VRAM + guard from the existing verify-stress output (both the thin-margin and ok lines), classifies it (thin < guard / marginal < 2× guard / comfortable), and the verify-stress report section prints e.g. "Ceiling VRAM margin: 1500 MB free (guard 1024 MB) — ⚠ marginal: ... a second run or server restart may OOM. Lower CTX_SIZE ...". rebench-report.py only — no change to verify-stress.sh's pass/fail logic. Validated parse on comfortable / marginal / thin / no-margin logs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
979 lines
40 KiB
Python
979 lines
40 KiB
Python
#!/usr/bin/env python3
|
||
"""rebench-report.py — synthesize REPORT.md from a results/rebench/<tag>/ dir.
|
||
|
||
Reads the raw logs and JSON artifacts that scripts/rebench-full.sh writes,
|
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extracts the structured numbers, and produces a single REPORT.md at the top
|
||
of the tag dir. Re-runnable standalone — just pass the tag-dir path.
|
||
|
||
Usage:
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python3 scripts/rebench-report.py results/rebench/<tag>/
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||
"""
|
||
|
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from __future__ import annotations
|
||
|
||
import argparse
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import json
|
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import re
|
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import subprocess
|
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import sys
|
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from collections import defaultdict
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from pathlib import Path
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from typing import Any
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||
|
||
|
||
# --- file readers -----------------------------------------------------------
|
||
|
||
def read_file(path: Path) -> str:
|
||
if not path.is_file():
|
||
return ""
|
||
try:
|
||
return path.read_text(errors="replace")
|
||
except Exception:
|
||
return ""
|
||
|
||
|
||
def read_json(path: Path) -> Any:
|
||
if not path.is_file():
|
||
return None
|
||
try:
|
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return json.loads(path.read_text(errors="replace"))
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||
except Exception:
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return None
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||
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||
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# --- section: meta + config -------------------------------------------------
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||
|
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def parse_container_config(blob: dict | None) -> dict:
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"""Pull the relevant bits from `docker inspect <container>`."""
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if not blob:
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||
return {}
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||
# docker inspect returns a list with one element
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if isinstance(blob, list) and blob:
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blob = blob[0]
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cfg = blob.get("Config", {}) or {}
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||
state = blob.get("State", {}) or {}
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||
mounts = blob.get("Mounts", [])
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cmd = cfg.get("Cmd") or []
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||
env = cfg.get("Env") or []
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||
|
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# extract flag values from Cmd list
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def get_flag(name: str) -> str | None:
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try:
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i = cmd.index(name)
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return cmd[i + 1]
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except (ValueError, IndexError):
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return None
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||
|
||
# mounts that look like vendored patches
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patches = []
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for m in mounts:
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src = m.get("Source", "")
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if "/patches/" in src and m.get("Type") == "bind":
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# take the patch dir name
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parts = src.split("/patches/")
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if len(parts) > 1:
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name = parts[1].split("/")[0]
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if name not in patches:
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patches.append(name)
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||
|
||
return {
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"image": cfg.get("Image"),
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"name": blob.get("Name", "").lstrip("/"),
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||
"status": state.get("Status"),
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"model": get_flag("--model") or "?",
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||
"served_model_name": get_flag("--served-model-name") or "?",
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||
"quantization": get_flag("--quantization") or "?",
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||
"dtype": get_flag("--dtype") or "?",
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"tensor_parallel_size": get_flag("--tensor-parallel-size") or "?",
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"max_model_len": get_flag("--max-model-len") or "?",
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"gpu_memory_utilization": get_flag("--gpu-memory-utilization") or "?",
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||
"max_num_seqs": get_flag("--max-num-seqs") or "?",
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"max_num_batched_tokens": get_flag("--max-num-batched-tokens") or "?",
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"kv_cache_dtype": get_flag("--kv-cache-dtype") or "?",
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||
"speculative_config": get_flag("--speculative-config") or "?",
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"patches": patches,
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"env": env,
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}
|
||
|
||
|
||
def parse_model_config_json(model_dir: Path) -> dict:
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"""Read config.json from the served model dir to get quant metadata."""
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cfg_path = model_dir / "config.json"
|
||
if not cfg_path.is_file():
|
||
return {}
|
||
blob = read_json(cfg_path)
|
||
if not blob:
|
||
return {}
|
||
q = blob.get("quantization_config") or {}
|
||
return {
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||
"model_type": blob.get("model_type"),
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||
"architectures": blob.get("architectures") or [],
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||
"quant_method": q.get("quant_method"),
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||
"bits": q.get("bits"),
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"group_size": q.get("group_size"),
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}
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||
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# --- section: vLLM boot log (KV pool + max concurrency) ---------------------
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def parse_vllm_boot(boot_log: str) -> dict:
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"""Pull KV cache size and Max concurrency lines."""
|
||
out = {}
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m = re.search(r"GPU KV cache size: ([\d,]+) tokens", boot_log)
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if m:
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out["kv_cache_tokens"] = int(m.group(1).replace(",", ""))
|
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m = re.search(r"Maximum concurrency for ([\d,]+) tokens per request: ([\d.]+)x", boot_log)
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if m:
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out["max_concurrency_request_size"] = int(m.group(1).replace(",", ""))
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out["max_concurrency"] = float(m.group(2))
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m = re.search(r"Available KV cache memory: ([\d.]+) GiB", boot_log)
|
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if m:
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out["available_kv_cache_gib"] = float(m.group(1))
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m = re.search(r"Model loading took ([\d.]+) GiB memory", boot_log)
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if m:
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||
out["model_load_gib"] = float(m.group(1))
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return out
|
||
|
||
|
||
# --- section: bench.sh ------------------------------------------------------
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||
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||
def parse_bench(log: str) -> dict:
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"""Extract narrative + code TPS summaries from bench.sh output."""
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out: dict[str, Any] = {}
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for kind in ("narrative", "code", "prompt-processing"):
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block = re.search(
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rf"=== summary \[{kind}\] \(n=\d+\) ===\s*\n"
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rf"(?P<body>.*?)(?=\n==========|\n=== GPU state ===|\n=== Last|\Z)",
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log,
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re.DOTALL,
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)
|
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if not block:
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continue
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body = block.group("body")
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parsed: dict[str, Any] = {}
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m = re.search(r"\s+wall_TPS\s+mean=\s*([\d.]+)\s+std=\s*([\d.]+)\s+CV=\s*([\d.]+)%", body)
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if m:
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parsed["wall_tps_mean"] = float(m.group(1))
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parsed["wall_tps_cv"] = float(m.group(3))
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m = re.search(r"\s+decode_TPS\s+mean=\s*([\d.]+)\s+std=\s*([\d.]+)\s+CV=\s*([\d.]+)%", body)
|
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if m:
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parsed["decode_tps_mean"] = float(m.group(1))
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parsed["decode_tps_cv"] = float(m.group(3))
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m = re.search(r"\s+TTFT\s+mean=\s*([\d.]+)ms", body)
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if m:
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parsed["ttft_ms_mean"] = float(m.group(1))
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m = re.search(r"\s+PP tok/s\s+mean=\s*([\d.]+)\s+std=\s*([\d.]+)\s+CV=\s*([\d.]+)%", body)
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if m:
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parsed["pp_tps_mean"] = float(m.group(1))
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parsed["pp_tps_cv"] = float(m.group(3))
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if parsed:
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out[kind.replace("-", "_")] = parsed
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# GPU state at end
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gpu_block = re.search(r"=== GPU state ===\s*\n((?:\d.+\n){1,4})", log)
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if gpu_block:
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gpu_lines = gpu_block.group(1).strip().split("\n")
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out["gpu_state"] = []
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for line in gpu_lines:
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parts = [p.strip() for p in line.split(",")]
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if len(parts) >= 6:
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out["gpu_state"].append({
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"idx": parts[0],
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"util_pct": parts[1],
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"mem_used": parts[2],
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"mem_total": parts[3],
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"power_w": parts[4],
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"temp_c": parts[5],
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})
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# MTP last metrics line
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mtp_lines = re.findall(
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r"Mean acceptance length: ([\d.]+), .* "
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r"Per-position acceptance rate: ([^,]+), .* "
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r"Avg Draft acceptance rate: ([\d.]+)%",
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log,
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)
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if mtp_lines:
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last = mtp_lines[-1]
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out["mtp"] = {
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||
"mean_accept_length": float(last[0]),
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||
"per_position": last[1].strip(),
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"avg_accept_rate": float(last[2]),
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||
}
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||
return out
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||
|
||
|
||
# --- section: verify-stress -------------------------------------------------
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||
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def parse_verify_stress(log: str) -> dict:
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"""Extract the 7-check verdict table."""
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checks = []
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# match lines like "[1/7] description ..." followed by ✓ or ✗
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for m in re.finditer(r"\[(\d+/\d+)\] (.+?) \.\.\.\n(.*?)(?=\n\[\d+/\d+\]|\nAll stress|\Z)", log, re.DOTALL):
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idx = m.group(1)
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desc = m.group(2).strip()
|
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body = m.group(3)
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||
verdict = "PASS" if "✓" in body else ("FAIL" if "✗" in body else "?")
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||
checks.append({"idx": idx, "desc": desc, "verdict": verdict})
|
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overall = "PASS" if "All stress / boundary checks passed" in log else (
|
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"FAIL" if any(c["verdict"] == "FAIL" for c in checks) else "?"
|
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)
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||
result = {"checks": checks, "overall": overall}
|
||
|
||
# Ceiling VRAM margin (#184). verify-stress.sh prints free VRAM at the
|
||
# deepest rung and hard-fails below the guard, but a margin that *passes*
|
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# the guard yet sits close to it can still OOM on a second run / server
|
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# restart (laurimyllari's marginal-but-passing case). Surface the number so
|
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# a PASS isn't mistaken for comfortable headroom.
|
||
free = thresh = None
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m_thin = re.search(r"VRAM margin thin at ceiling:\s*(\d+)\s*MB free\s*<\s*(\d+)\s*MB", log)
|
||
if m_thin:
|
||
free, thresh = int(m_thin.group(1)), int(m_thin.group(2))
|
||
else:
|
||
m_ok = re.search(r"VRAM:\s*\d+\s*\S+\s*(\d+)\s*MB[^\n]*margin threshold=(\d+)", log)
|
||
if m_ok:
|
||
free, thresh = int(m_ok.group(1)), int(m_ok.group(2))
|
||
if free is not None and thresh:
|
||
result["ceiling_vram_free_mb"] = free
|
||
result["vram_threshold_mb"] = thresh
|
||
result["vram_status"] = (
|
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"thin" if free < thresh else "marginal" if free < 2 * thresh else "comfortable"
|
||
)
|
||
return result
|
||
|
||
|
||
# --- section: quality-full --------------------------------------------------
|
||
|
||
def parse_quality(blob: dict | None) -> dict:
|
||
if not blob:
|
||
return {}
|
||
packs = []
|
||
failure_examples: dict[str, list[str]] = defaultdict(list)
|
||
for p in blob.get("packs", []):
|
||
if p.get("pack_id") == "aider-polyglot-30":
|
||
continue # rendered separately
|
||
lat = p.get("latency") or {}
|
||
packs.append({
|
||
"pack_id": p.get("pack_id"),
|
||
"passed": p.get("passed"),
|
||
"total": p.get("total"),
|
||
"score_pct": round(100 * (p.get("score") or 0)),
|
||
"p50_latency_s": lat.get("p50") if isinstance(lat, dict) else None,
|
||
"p95_latency_s": lat.get("p95") if isinstance(lat, dict) else None,
|
||
"mean_latency_s": lat.get("mean") if isinstance(lat, dict) else None,
|
||
"status": p.get("status"),
|
||
})
|
||
# gather top-3 failures per pack for the report appendix
|
||
for s in (p.get("scenarios") or []):
|
||
if not s.get("passed", True):
|
||
pack = p.get("pack_id", "?")
|
||
sid = s.get("id") or (s.get("raw_scenario") or {}).get("id", "?")
|
||
fail = s.get("failure_mode") or "?"
|
||
detail = (s.get("detail") or "")[:140]
|
||
if len(failure_examples[pack]) < 3:
|
||
failure_examples[pack].append(f"{sid}: {fail} — {detail}")
|
||
total_passed = sum(p["passed"] or 0 for p in packs)
|
||
total_total = sum(p["total"] or 0 for p in packs)
|
||
return {
|
||
"packs": packs,
|
||
"total_passed": total_passed,
|
||
"total_total": total_total,
|
||
"total_pct": round(100 * total_passed / max(total_total, 1)),
|
||
"failure_examples": dict(failure_examples),
|
||
}
|
||
|
||
|
||
# --- section: soak ----------------------------------------------------------
|
||
|
||
def parse_soak(log: str) -> dict:
|
||
out = {}
|
||
for key in ("verdict", "max_growth_mib", "errors", "silent_empty",
|
||
"p50_decode_tps", "p95_ttft_ms", "tps_retention", "boot_vram_mib"):
|
||
m = re.search(rf"\b{key}\b\s+(\S.+)$", log, re.MULTILINE)
|
||
if m:
|
||
out[key] = m.group(1).strip()
|
||
return out
|
||
|
||
|
||
# --- section: aider-polyglot ------------------------------------------------
|
||
|
||
def parse_aider(blob: dict | None) -> dict:
|
||
"""upstream_per_exercise can be either:
|
||
- dict keyed by '<lang>/<exercise>' (current shape from aider's benchmark.py)
|
||
- list of {language, passed} dicts (older or alt shape)
|
||
Handle both.
|
||
"""
|
||
if not blob:
|
||
return {}
|
||
for p in blob.get("packs", []):
|
||
if p.get("pack_id") != "aider-polyglot-30":
|
||
continue
|
||
s = (p.get("scenarios") or [{}])[0]
|
||
latency_s = s.get("latency_seconds")
|
||
trace = s.get("verifier_trace", {})
|
||
# Schema v3 nests the trace under .trace; older versions are flat.
|
||
inner = trace.get("trace", trace) or {}
|
||
per_ex = inner.get("upstream_per_exercise") or inner.get("per_exercise") or {}
|
||
|
||
per_lang: dict = defaultdict(lambda: [0, 0])
|
||
passed_total = 0
|
||
total = 0
|
||
|
||
if isinstance(per_ex, dict):
|
||
# current shape: keyed by "<lang>/<exercise>"
|
||
for path, entry in per_ex.items():
|
||
lang = path.split("/", 1)[0].lower() if "/" in path else "?"
|
||
per_lang[lang][1] += 1
|
||
total += 1
|
||
if entry.get("passed") is True or entry.get("tests_passed") is True \
|
||
or entry.get("status") == "pass":
|
||
per_lang[lang][0] += 1
|
||
passed_total += 1
|
||
elif isinstance(per_ex, list):
|
||
for entry in per_ex:
|
||
lang = (entry.get("language") or "?").lower()
|
||
per_lang[lang][1] += 1
|
||
total += 1
|
||
if entry.get("passed") is True or entry.get("status") == "pass":
|
||
per_lang[lang][0] += 1
|
||
passed_total += 1
|
||
|
||
# Prefer the top-level fields if they're set; fall back to our tally.
|
||
passed_count = s.get("passed_count") if s.get("passed_count") is not None else passed_total
|
||
total_count = s.get("total_count") if s.get("total_count") is not None else total
|
||
pass_rate = s.get("pass_rate")
|
||
if pass_rate is None and total_count:
|
||
pass_rate = passed_count / total_count
|
||
|
||
return {
|
||
"pass_rate": pass_rate,
|
||
"passed_count": passed_count,
|
||
"total_count": total_count,
|
||
"wall_seconds": latency_s,
|
||
"per_language": dict(per_lang),
|
||
"aider_commit": inner.get("aider_pinned_commit", ""),
|
||
"polyglot_commit": inner.get("polyglot_pinned_commit", ""),
|
||
"edit_format": inner.get("edit_format", ""),
|
||
}
|
||
return {}
|
||
|
||
|
||
# --- markdown rendering -----------------------------------------------------
|
||
|
||
def render(report: dict) -> str:
|
||
lines = []
|
||
lines.append(f"# Rebench report — {report.get('tag', '?')}")
|
||
lines.append("")
|
||
lines.append(f"_Generated by `scripts/rebench-report.py` from `{report.get('tag_dir')}`_")
|
||
lines.append("")
|
||
|
||
# --- headline TL;DR (auto-computed from data) ---
|
||
tldr = report.get("tldr", [])
|
||
if tldr:
|
||
lines.append("## TL;DR")
|
||
lines.append("")
|
||
for bullet in tldr:
|
||
lines.append(f"- {bullet}")
|
||
lines.append("")
|
||
|
||
# --- meta ---
|
||
meta = report.get("meta", {})
|
||
lines.append("## Meta")
|
||
lines.append("")
|
||
lines.append(f"- **Tag:** `{report.get('tag', '?')}`")
|
||
lines.append(f"- **Date:** {report.get('date', '?')}")
|
||
lines.append(f"- **Repo commit:** `{report.get('commit_sha', '?')}`")
|
||
if meta.get("model_config"):
|
||
mc = meta["model_config"]
|
||
lines.append(f"- **Model arch:** {mc.get('model_type', '?')} ({(mc.get('architectures') or ['?'])[0]})")
|
||
lines.append(f"- **Quant:** {mc.get('quant_method', '?')} {mc.get('bits', '?')}-bit, group_size {mc.get('group_size', '?')}")
|
||
if meta.get("container"):
|
||
c = meta["container"]
|
||
lines.append(f"- **Served as:** `{c.get('served_model_name')}` from `{c.get('model')}`")
|
||
lines.append(f"- **vLLM image:** `{c.get('image')}`")
|
||
lines.append(f"- **Container:** `{c.get('name')}`")
|
||
rig = meta.get("rig", {})
|
||
if rig:
|
||
if rig.get("hostname"):
|
||
lines.append(f"- **Rig hostname:** `{rig['hostname']}`")
|
||
if rig.get("gpus"):
|
||
lines.append(f"- **GPUs:** {', '.join(rig['gpus'])}")
|
||
if rig.get("power_cap_w"):
|
||
lines.append(f"- **Power cap:** {rig['power_cap_w']} W/card")
|
||
lines.append("")
|
||
|
||
# --- config ---
|
||
lines.append("## Config")
|
||
lines.append("")
|
||
if meta.get("container"):
|
||
c = meta["container"]
|
||
lines.append("| Setting | Value |")
|
||
lines.append("|---|---|")
|
||
lines.append(f"| `--tensor-parallel-size` | {c.get('tensor_parallel_size')} |")
|
||
lines.append(f"| `--max-model-len` | {c.get('max_model_len')} |")
|
||
lines.append(f"| `--gpu-memory-utilization` | {c.get('gpu_memory_utilization')} |")
|
||
lines.append(f"| `--max-num-seqs` | {c.get('max_num_seqs')} |")
|
||
lines.append(f"| `--max-num-batched-tokens` | {c.get('max_num_batched_tokens')} |")
|
||
lines.append(f"| `--kv-cache-dtype` | `{c.get('kv_cache_dtype')}` |")
|
||
lines.append(f"| `--dtype` | `{c.get('dtype')}` |")
|
||
lines.append(f"| `--quantization` | `{c.get('quantization')}` |")
|
||
lines.append(f"| `--speculative-config` | `{c.get('speculative_config')}` |")
|
||
patches = c.get("patches") or []
|
||
lines.append(f"| Patches mounted | {', '.join(f'`{p}`' for p in patches) if patches else 'none'} |")
|
||
# Genesis detection
|
||
genesis_envs = [e for e in (c.get("env") or []) if e.startswith("GENESIS_")]
|
||
lines.append(f"| Genesis | {'on (' + str(len(genesis_envs)) + ' GENESIS_* env vars)' if genesis_envs else 'none'} |")
|
||
lines.append("")
|
||
|
||
# --- bench performance ---
|
||
bench = report.get("bench", {})
|
||
lines.append("## Performance — `bench.sh`")
|
||
lines.append("")
|
||
if bench.get("narrative") or bench.get("code"):
|
||
lines.append("| Bench | wall TPS | decode TPS | PP tok/s | TTFT | CV (wall/decode) |")
|
||
lines.append("|---|---:|---:|---:|---:|---:|")
|
||
for kind in ("narrative", "code"):
|
||
b = bench.get(kind)
|
||
if b:
|
||
pp = f"{b['pp_tps_mean']:.0f}" if b.get("pp_tps_mean") is not None else "n/a"
|
||
lines.append(
|
||
f"| {kind} | {b['wall_tps_mean']:.2f} | **{b['decode_tps_mean']:.2f}** | {pp} | "
|
||
f"{b['ttft_ms_mean']:.0f} ms | {b['wall_tps_cv']:.1f}% / {b['decode_tps_cv']:.1f}% |"
|
||
)
|
||
pp_fallback = bench.get("prompt_processing")
|
||
if pp_fallback and pp_fallback.get("pp_tps_mean") is not None:
|
||
lines.append(
|
||
f"| prompt-processing fallback | — | — | **{pp_fallback['pp_tps_mean']:.0f}** | "
|
||
f"{pp_fallback.get('ttft_ms_mean', 0):.0f} ms | — |"
|
||
)
|
||
if bench.get("mtp"):
|
||
m = bench["mtp"]
|
||
lines.append("")
|
||
lines.append(f"**MTP (warm, last metric):** mean accept length {m['mean_accept_length']:.2f}, "
|
||
f"avg accept rate {m['avg_accept_rate']:.1f}%, per-position {m['per_position']}")
|
||
if bench.get("gpu_state"):
|
||
lines.append("")
|
||
lines.append("**GPU state at bench end:**")
|
||
lines.append("")
|
||
lines.append("| GPU | Util | Mem used / total | Power | Temp |")
|
||
lines.append("|---|---|---|---|---|")
|
||
for g in bench["gpu_state"]:
|
||
lines.append(f"| {g['idx']} | {g['util_pct']} | {g['mem_used']} / {g['mem_total']} | {g['power_w']} | {g['temp_c']} |")
|
||
else:
|
||
lines.append("_(bench artifacts missing)_")
|
||
lines.append("")
|
||
|
||
# --- concurrency + VRAM ---
|
||
boot = report.get("vllm_boot", {})
|
||
lines.append("## Concurrency + VRAM")
|
||
lines.append("")
|
||
if boot:
|
||
kv_tokens = boot.get("kv_cache_tokens")
|
||
max_conc = boot.get("max_concurrency")
|
||
req_size = boot.get("max_concurrency_request_size")
|
||
avail = boot.get("available_kv_cache_gib")
|
||
model_load = boot.get("model_load_gib")
|
||
lines.append("| Metric | Value |")
|
||
lines.append("|---|---:|")
|
||
if model_load:
|
||
lines.append(f"| Model load footprint | {model_load:.2f} GiB |")
|
||
if avail:
|
||
lines.append(f"| Available KV cache memory (per card, post-profiling) | {avail:.2f} GiB |")
|
||
if kv_tokens:
|
||
lines.append(f"| GPU KV cache size | **{kv_tokens:,} tokens** |")
|
||
if max_conc and req_size:
|
||
lines.append(f"| Max concurrency @ {req_size:,} tokens/req | **{max_conc:.2f}×** |")
|
||
if req_size > 1:
|
||
for ctx in (100_000, 32_000):
|
||
practical = max_conc * (req_size / ctx)
|
||
lines.append(f"| Practical concurrency @ {ctx:,} tokens/req | ~{practical:.1f}× |")
|
||
else:
|
||
lines.append("_(no vLLM boot log captured)_")
|
||
lines.append("")
|
||
|
||
# --- verify-stress ---
|
||
stress = report.get("verify_stress", {})
|
||
lines.append("## Verify-stress — 7-check boundary matrix")
|
||
lines.append("")
|
||
if stress.get("checks"):
|
||
lines.append(f"**Overall:** {stress.get('overall')}")
|
||
lines.append("")
|
||
lines.append("| # | Check | Verdict |")
|
||
lines.append("|---|---|---|")
|
||
for c in stress["checks"]:
|
||
lines.append(f"| {c['idx']} | {c['desc']} | {c['verdict']} |")
|
||
if stress.get("ceiling_vram_free_mb") is not None:
|
||
free = stress["ceiling_vram_free_mb"]
|
||
thresh = stress["vram_threshold_mb"]
|
||
note = {
|
||
"thin": " — ⚠ **THIN** (below the sustained-agent guard; verify-stress fails this check)",
|
||
"marginal": " — ⚠ **marginal**: within 2× the guard, so a second run or server restart may OOM. Lower `CTX_SIZE` for sustained agent load.",
|
||
"comfortable": " — ✓ comfortable",
|
||
}[stress["vram_status"]]
|
||
lines.append("")
|
||
lines.append(f"**Ceiling VRAM margin:** {free} MB free (guard {thresh} MB){note}")
|
||
else:
|
||
lines.append("_(verify-stress log missing or unparsed)_")
|
||
lines.append("")
|
||
|
||
# --- quality ---
|
||
quality = report.get("quality", {})
|
||
lines.append("## Quality — `quality-test.sh --full`")
|
||
lines.append("")
|
||
if quality.get("packs"):
|
||
lines.append("| Pack | Pass / Total | Score | p50 latency | p95 latency |")
|
||
lines.append("|---|---:|---:|---:|---:|")
|
||
for p in quality["packs"]:
|
||
p50 = f"{p['p50_latency_s']:.2f}s" if p.get("p50_latency_s") is not None else "—"
|
||
p95 = f"{p['p95_latency_s']:.2f}s" if p.get("p95_latency_s") is not None else "—"
|
||
lines.append(f"| {p['pack_id']} | {p['passed']} / {p['total']} | {p['score_pct']}% | {p50} | {p95} |")
|
||
lines.append(f"| **TOTAL** | **{quality['total_passed']} / {quality['total_total']}** | **{quality['total_pct']}%** | | |")
|
||
if quality.get("one_liner"):
|
||
lines.append("")
|
||
lines.append("**Paste-ready compose `Quality:` schema line:**")
|
||
lines.append("```")
|
||
lines.append(quality["one_liner"])
|
||
lines.append("```")
|
||
if quality.get("failure_examples"):
|
||
lines.append("")
|
||
lines.append("**Failure examples (top 3 per pack):**")
|
||
for pack, examples in sorted(quality["failure_examples"].items()):
|
||
lines.append(f"- `{pack}`:")
|
||
for ex in examples:
|
||
lines.append(f" - {ex}")
|
||
else:
|
||
lines.append("_(quality JSON missing or unparsed)_")
|
||
lines.append("")
|
||
|
||
# --- soak ---
|
||
soak = report.get("soak", {})
|
||
lines.append("## Soak — `soak-test.sh`")
|
||
lines.append("")
|
||
if soak:
|
||
lines.append("| Metric | Value |")
|
||
lines.append("|---|---|")
|
||
for k in ("verdict", "silent_empty", "p50_decode_tps", "p95_ttft_ms",
|
||
"tps_retention", "max_growth_mib", "errors", "boot_vram_mib"):
|
||
if k in soak:
|
||
lines.append(f"| `{k}` | {soak[k]} |")
|
||
else:
|
||
lines.append("_(soak log missing or unparsed)_")
|
||
lines.append("")
|
||
|
||
# --- aider-polyglot ---
|
||
aider = report.get("aider", {})
|
||
lines.append("## Aider Polyglot 30 — per-language breakdown")
|
||
lines.append("")
|
||
if aider.get("per_language"):
|
||
lines.append(f"**Total:** {aider.get('passed_count', '?')} / {aider.get('total_count', '?')} "
|
||
f"({100 * (aider.get('pass_rate') or 0):.1f}%) · "
|
||
f"wall {aider.get('wall_seconds', 0):.0f}s")
|
||
lines.append("")
|
||
lines.append("| Language | Pass / Total | Score |")
|
||
lines.append("|---|---:|---:|")
|
||
for lang, (passed, total) in sorted(aider["per_language"].items()):
|
||
pct = round(100 * passed / total) if total else 0
|
||
lines.append(f"| {lang} | {passed} / {total} | {pct}% |")
|
||
else:
|
||
lines.append("_(aider-polyglot artifacts missing or no per-exercise trace)_")
|
||
lines.append("")
|
||
|
||
# --- phase timings ---
|
||
timings = report.get("timings", {})
|
||
if timings:
|
||
lines.append("## Phase timings")
|
||
lines.append("")
|
||
lines.append("| Phase | Duration |")
|
||
lines.append("|---|---:|")
|
||
total_s = 0
|
||
for phase, secs in timings.items():
|
||
if isinstance(secs, (int, float)) and secs > 0:
|
||
m, s = divmod(int(secs), 60)
|
||
lines.append(f"| {phase} | {m}m {s}s |")
|
||
total_s += secs
|
||
if total_s:
|
||
tm, ts = divmod(int(total_s), 60)
|
||
lines.append(f"| **Total** | **{tm}m {ts}s** |")
|
||
lines.append("")
|
||
|
||
# --- reproducer ---
|
||
repro = report.get("reproducer", {})
|
||
if repro:
|
||
lines.append("## Reproduce on your rig")
|
||
lines.append("")
|
||
lines.append("```bash")
|
||
for line in repro.get("commands", []):
|
||
lines.append(line)
|
||
lines.append("```")
|
||
lines.append("")
|
||
|
||
# --- delta vs prior tag (when --compare-to given) ---
|
||
delta = report.get("delta", {})
|
||
if delta:
|
||
lines.append(f"## Delta vs `{delta.get('compare_to', '?')}`")
|
||
lines.append("")
|
||
for section, rows in delta.get("sections", {}).items():
|
||
if rows:
|
||
lines.append(f"### {section}")
|
||
lines.append("")
|
||
lines.append("| Metric | this | prior | Δ |")
|
||
lines.append("|---|---:|---:|---:|")
|
||
for r in rows:
|
||
lines.append(f"| {r['metric']} | {r['this']} | {r['prior']} | {r['delta']} |")
|
||
lines.append("")
|
||
|
||
return "\n".join(lines)
|
||
|
||
|
||
def render_discuss(report: dict) -> str:
|
||
"""Trimmed variant for posting under a GitHub Discussion comment.
|
||
Drops failure examples + bench raw GPU table; keeps the headline tables."""
|
||
lines = []
|
||
lines.append(f"**Rebench — {report.get('tag', '?')}**")
|
||
lines.append("")
|
||
if report.get("tldr"):
|
||
for b in report["tldr"]:
|
||
lines.append(f"- {b}")
|
||
lines.append("")
|
||
meta = report.get("meta", {})
|
||
c = meta.get("container", {})
|
||
if c:
|
||
# Quant string: prefer model_config bits, fall back to quantization scheme name.
|
||
mc = meta.get("model_config", {}) or {}
|
||
quant_str = f"{mc.get('quant_method', c.get('quantization', '?'))} {mc.get('bits', '?')}-bit" \
|
||
if mc.get("bits") else c.get("quantization", "?")
|
||
lines.append(f"Config: `{c.get('image')}` · {quant_str} · "
|
||
f"`{c.get('kv_cache_dtype')}` KV · `{c.get('max_model_len')}` ctx · "
|
||
f"`{c.get('speculative_config')}` · TP={c.get('tensor_parallel_size')}")
|
||
lines.append("")
|
||
# bench
|
||
bench = report.get("bench", {})
|
||
if bench.get("narrative"):
|
||
b_n, b_c = bench["narrative"], bench.get("code", {})
|
||
lines.append("**TPS:**")
|
||
pp_n = f", PP {b_n['pp_tps_mean']:.0f} tok/s" if b_n.get("pp_tps_mean") is not None else ""
|
||
lines.append(f"- Narrative: {b_n['decode_tps_mean']:.1f} TPS decode, {b_n['ttft_ms_mean']:.0f} ms TTFT{pp_n} (CV {b_n['decode_tps_cv']:.1f}%)")
|
||
if b_c:
|
||
pp_c = f", PP {b_c['pp_tps_mean']:.0f} tok/s" if b_c.get("pp_tps_mean") is not None else ""
|
||
lines.append(f"- Code: {b_c['decode_tps_mean']:.1f} TPS decode, {b_c['ttft_ms_mean']:.0f} ms TTFT{pp_c} (CV {b_c['decode_tps_cv']:.1f}%)")
|
||
if bench.get("prompt_processing", {}).get("pp_tps_mean") is not None:
|
||
pp = bench["prompt_processing"]["pp_tps_mean"]
|
||
lines.append(f"- Prompt-processing fallback: {pp:.0f} tok/s")
|
||
lines.append("")
|
||
boot = report.get("vllm_boot", {})
|
||
if boot.get("kv_cache_tokens"):
|
||
lines.append(f"**Concurrency:** GPU KV pool **{boot['kv_cache_tokens']:,} tokens**, "
|
||
f"**{boot.get('max_concurrency', 0):.2f}×** concurrency @ {boot.get('max_concurrency_request_size', 0):,} tokens/req.")
|
||
lines.append("")
|
||
stress = report.get("verify_stress", {})
|
||
if stress.get("checks"):
|
||
passed = sum(1 for c in stress["checks"] if c["verdict"] == "PASS")
|
||
total = len(stress["checks"])
|
||
lines.append(f"**Stress:** {passed}/{total} checks PASS.")
|
||
lines.append("")
|
||
q = report.get("quality", {})
|
||
if q.get("packs"):
|
||
rows = " · ".join(f"{p['pack_id']} {p['passed']}/{p['total']} ({p['score_pct']}%)" for p in q["packs"])
|
||
lines.append(f"**Quality:** {q['total_passed']}/{q['total_total']} ({q['total_pct']}%) — {rows}")
|
||
lines.append("")
|
||
soak = report.get("soak", {})
|
||
if soak:
|
||
lines.append(f"**Soak:** verdict {soak.get('verdict', '?')}, "
|
||
f"silent_empty {soak.get('silent_empty', '?')}, "
|
||
f"p50 decode {soak.get('p50_decode_tps', '?')} TPS.")
|
||
lines.append("")
|
||
aider = report.get("aider", {})
|
||
if aider.get("per_language"):
|
||
per_lang_str = " · ".join(f"{l} {p}/{t}" for l, (p, t) in sorted(aider["per_language"].items()))
|
||
lines.append(f"**Aider-polyglot:** {aider.get('passed_count', '?')}/{aider.get('total_count', '?')} — {per_lang_str}")
|
||
lines.append("")
|
||
return "\n".join(lines)
|
||
|
||
|
||
# --- helpers for the new sections -------------------------------------------
|
||
|
||
def compute_tldr(report: dict) -> list[str]:
|
||
"""Auto-generate 3-5 punchy bullets from the parsed data."""
|
||
bullets = []
|
||
bench = report.get("bench", {})
|
||
if bench.get("narrative") and bench.get("code"):
|
||
pp_vals = [
|
||
b.get("pp_tps_mean")
|
||
for b in (bench.get("narrative", {}), bench.get("code", {}))
|
||
if b.get("pp_tps_mean") is not None
|
||
]
|
||
pp_text = f", PP {sum(pp_vals) / len(pp_vals):.0f} tok/s" if pp_vals else ""
|
||
bullets.append(
|
||
f"TPS narrative **{bench['narrative']['decode_tps_mean']:.1f}** / "
|
||
f"code **{bench['code']['decode_tps_mean']:.1f}** "
|
||
f"(TTFT {bench['narrative']['ttft_ms_mean']:.0f}/{bench['code']['ttft_ms_mean']:.0f} ms{pp_text})."
|
||
)
|
||
elif bench.get("prompt_processing"):
|
||
pp = bench["prompt_processing"].get("pp_tps_mean")
|
||
if pp is not None:
|
||
bullets.append(f"Prompt processing fallback: **{pp:.0f} tok/s**.")
|
||
boot = report.get("vllm_boot", {})
|
||
if boot.get("kv_cache_tokens") and boot.get("max_concurrency"):
|
||
bullets.append(
|
||
f"KV pool **{boot['kv_cache_tokens']:,} tokens** — "
|
||
f"**{boot['max_concurrency']:.2f}×** concurrency @ {boot.get('max_concurrency_request_size', 0):,} tokens/req."
|
||
)
|
||
stress = report.get("verify_stress", {})
|
||
if stress.get("checks"):
|
||
passed = sum(1 for c in stress["checks"] if c["verdict"] == "PASS")
|
||
total = len(stress["checks"])
|
||
bullets.append(f"Verify-stress: **{passed}/{total}** boundary checks PASS.")
|
||
q = report.get("quality", {})
|
||
if q.get("total_total"):
|
||
bullets.append(
|
||
f"Quality (8 packs, {q['total_total']} scenarios): **{q['total_passed']}/{q['total_total']} ({q['total_pct']}%)**."
|
||
)
|
||
soak = report.get("soak", {})
|
||
if soak.get("verdict"):
|
||
bullets.append(
|
||
f"Soak: **{soak['verdict']}** — silent_empty {soak.get('silent_empty', '?')}, "
|
||
f"p50 decode {soak.get('p50_decode_tps', '?')} TPS."
|
||
)
|
||
a = report.get("aider", {})
|
||
if a.get("total_count"):
|
||
bullets.append(
|
||
f"Aider-polyglot: **{a.get('passed_count', '?')}/{a['total_count']}** "
|
||
f"({100 * (a.get('pass_rate') or 0):.1f}%) — per-lang in section below."
|
||
)
|
||
return bullets
|
||
|
||
|
||
def parse_rig(rig_txt: str) -> dict:
|
||
"""Parse rig.txt captured by rebench-full.sh.
|
||
Format: free-form key: value lines from `nvidia-smi -L`, hostname, etc."""
|
||
rig = {"gpus": []}
|
||
for line in rig_txt.splitlines():
|
||
line = line.strip()
|
||
if not line:
|
||
continue
|
||
if line.startswith("hostname:"):
|
||
rig["hostname"] = line.split(":", 1)[1].strip()
|
||
elif line.startswith("GPU "):
|
||
# `nvidia-smi -L` format: "GPU 0: NVIDIA GeForce RTX 3090 (UUID: GPU-xxx)"
|
||
rig["gpus"].append(line.split(":", 1)[1].split("(UUID")[0].strip())
|
||
elif line.startswith("power_cap_w:"):
|
||
rig["power_cap_w"] = line.split(":", 1)[1].strip()
|
||
return rig
|
||
|
||
|
||
def compute_reproducer(meta: dict) -> dict:
|
||
"""Render bash commands to re-run this exact config."""
|
||
c = meta.get("container", {})
|
||
cmds = []
|
||
if c.get("image"):
|
||
cmds.append("# Same vLLM nightly + KV class + ctx + MTP n as this run:")
|
||
cmds.append(f"# image: {c['image']}")
|
||
cmds.append("")
|
||
cmds.append("# Bring the model up via gpu-mode (or docker compose -f <compose>.yml up -d):")
|
||
cmds.append(f"# served_model_name = {c.get('served_model_name', '?')}")
|
||
cmds.append("")
|
||
cmds.append("bash scripts/rebench-full.sh")
|
||
cmds.append("")
|
||
cmds.append("# Or run individual phases:")
|
||
cmds.append("bash scripts/bench.sh # TPS")
|
||
cmds.append("bash scripts/verify-stress.sh # boundary")
|
||
cmds.append("bash scripts/quality-test.sh --full # 8-pack quality")
|
||
cmds.append("bash scripts/soak-test.sh # stability")
|
||
cmds.append("bash scripts/quality-test.sh --pack aider-polyglot-30")
|
||
return {"commands": cmds}
|
||
|
||
|
||
def compute_delta(this_report: dict, other_dir: Path) -> dict:
|
||
"""Diff this report against another tag dir's REPORT.md numerical fields."""
|
||
other_blob = read_json(other_dir / "_internal.json")
|
||
if not other_blob:
|
||
return {}
|
||
sections = {}
|
||
|
||
def num(v):
|
||
try:
|
||
return float(v)
|
||
except (TypeError, ValueError):
|
||
return None
|
||
|
||
def diff_row(label, a, b, unit=""):
|
||
an, bn = num(a), num(b)
|
||
if an is None or bn is None:
|
||
return None
|
||
d = an - bn
|
||
sign = "+" if d > 0 else ""
|
||
return {"metric": label, "this": f"{an:.2f}{unit}", "prior": f"{bn:.2f}{unit}",
|
||
"delta": f"{sign}{d:.2f}{unit}"}
|
||
|
||
perf_rows = []
|
||
for kind in ("narrative", "code"):
|
||
t = (this_report.get("bench", {}) or {}).get(kind, {})
|
||
o = (other_blob.get("bench", {}) or {}).get(kind, {})
|
||
if t and o:
|
||
r = diff_row(f"{kind} decode TPS", t.get("decode_tps_mean"), o.get("decode_tps_mean"))
|
||
if r: perf_rows.append(r)
|
||
r = diff_row(f"{kind} TTFT", t.get("ttft_ms_mean"), o.get("ttft_ms_mean"), " ms")
|
||
if r: perf_rows.append(r)
|
||
sections["Performance"] = perf_rows
|
||
|
||
conc_rows = []
|
||
t = this_report.get("vllm_boot", {})
|
||
o = other_blob.get("vllm_boot", {})
|
||
r = diff_row("GPU KV cache tokens", t.get("kv_cache_tokens"), o.get("kv_cache_tokens"))
|
||
if r: conc_rows.append(r)
|
||
r = diff_row("Max concurrency", t.get("max_concurrency"), o.get("max_concurrency"), "×")
|
||
if r: conc_rows.append(r)
|
||
sections["Concurrency"] = conc_rows
|
||
|
||
qual_rows = []
|
||
t = this_report.get("quality", {})
|
||
o = other_blob.get("quality", {})
|
||
r = diff_row("Total passes", t.get("total_passed"), o.get("total_passed"))
|
||
if r: qual_rows.append(r)
|
||
r = diff_row("Total %", t.get("total_pct"), o.get("total_pct"), "%")
|
||
if r: qual_rows.append(r)
|
||
sections["Quality"] = qual_rows
|
||
|
||
aid_rows = []
|
||
t = this_report.get("aider", {})
|
||
o = other_blob.get("aider", {})
|
||
r = diff_row("aider-polyglot passes", t.get("passed_count"), o.get("passed_count"))
|
||
if r: aid_rows.append(r)
|
||
sections["Aider Polyglot"] = aid_rows
|
||
|
||
return {"compare_to": other_dir.name, "sections": sections}
|
||
|
||
|
||
# --- main -------------------------------------------------------------------
|
||
|
||
def extract_date(tag_dir: Path) -> str:
|
||
"""Tag-dir date: look for YYYY-MM-DD or YYYYMMDD anywhere in the name,
|
||
otherwise fall back to the dir mtime."""
|
||
m = re.search(r"(\d{4}-\d{2}-\d{2}|\d{8})", tag_dir.name)
|
||
if m:
|
||
s = m.group(1)
|
||
if len(s) == 8:
|
||
return f"{s[:4]}-{s[4:6]}-{s[6:8]}"
|
||
return s
|
||
import datetime
|
||
return datetime.datetime.utcfromtimestamp(tag_dir.stat().st_mtime).strftime("%Y-%m-%d")
|
||
|
||
|
||
def extract_quality_oneliner(qfull_log: str) -> str | None:
|
||
"""Grep the paste-ready Quality: line from quality-test.sh stdout."""
|
||
for line in qfull_log.splitlines():
|
||
if line.lstrip().startswith("Quality:"):
|
||
return line.strip()
|
||
return None
|
||
|
||
|
||
def main(argv=None):
|
||
p = argparse.ArgumentParser()
|
||
p.add_argument("tag_dir", help="results/rebench/<tag>/ directory")
|
||
p.add_argument("--compare-to", default=None,
|
||
help="another tag dir to compute deltas against")
|
||
p.add_argument("--no-discuss", action="store_true",
|
||
help="skip writing REPORT-discuss.md")
|
||
args = p.parse_args(argv)
|
||
|
||
tag_dir = Path(args.tag_dir).resolve()
|
||
if not tag_dir.is_dir():
|
||
print(f"✗ not a directory: {tag_dir}", file=sys.stderr)
|
||
return 2
|
||
|
||
bench_log = read_file(tag_dir / "bench.log")
|
||
stress_log = read_file(tag_dir / "verify-stress.log")
|
||
quality_blob = read_json(tag_dir / "quality-full.json")
|
||
quality_log = read_file(tag_dir / "quality-full.log")
|
||
soak_log = read_file(tag_dir / "soak.log")
|
||
aider_blob = read_json(tag_dir / "aider-polyglot.json")
|
||
container_blob = read_json(tag_dir / "container-config.json")
|
||
boot_log = read_file(tag_dir / "vllm-boot.log")
|
||
timings_blob = read_json(tag_dir / "timings.json") or {}
|
||
rig_txt = read_file(tag_dir / "rig.txt")
|
||
|
||
# find model dir for quant config
|
||
model_config = {}
|
||
if container_blob:
|
||
cinfo = parse_container_config(container_blob)
|
||
model_path = cinfo.get("model", "")
|
||
if model_path and model_path.startswith("/root/.cache/huggingface/"):
|
||
host_path = Path("/mnt/models/huggingface") / Path(model_path).name
|
||
model_config = parse_model_config_json(host_path)
|
||
|
||
# commit SHA from the club-3090 repo (walk up to find .git)
|
||
sha_dir = tag_dir
|
||
while sha_dir != sha_dir.parent and not (sha_dir / ".git").exists():
|
||
sha_dir = sha_dir.parent
|
||
commit_sha = subprocess.run(
|
||
["git", "rev-parse", "--short", "HEAD"],
|
||
cwd=str(sha_dir if (sha_dir / ".git").exists() else tag_dir),
|
||
capture_output=True, text=True,
|
||
).stdout.strip() or "?"
|
||
|
||
quality = parse_quality(quality_blob)
|
||
one_liner = extract_quality_oneliner(quality_log)
|
||
if one_liner:
|
||
quality["one_liner"] = one_liner
|
||
|
||
report = {
|
||
"tag": tag_dir.name,
|
||
"tag_dir": str(tag_dir),
|
||
"date": extract_date(tag_dir),
|
||
"commit_sha": commit_sha,
|
||
"meta": {
|
||
"container": parse_container_config(container_blob),
|
||
"model_config": model_config,
|
||
"rig": parse_rig(rig_txt),
|
||
},
|
||
"vllm_boot": parse_vllm_boot(boot_log),
|
||
"bench": parse_bench(bench_log),
|
||
"verify_stress": parse_verify_stress(stress_log),
|
||
"quality": quality,
|
||
"soak": parse_soak(soak_log),
|
||
"aider": parse_aider(aider_blob),
|
||
"timings": timings_blob,
|
||
}
|
||
|
||
# auto-compute TL;DR
|
||
report["tldr"] = compute_tldr(report)
|
||
report["reproducer"] = compute_reproducer(report.get("meta", {}))
|
||
|
||
# optional delta vs prior tag
|
||
if args.compare_to:
|
||
other = Path(args.compare_to).resolve()
|
||
if other.is_dir():
|
||
report["delta"] = compute_delta(report, other)
|
||
|
||
# write a sidecar with the parsed numbers so future --compare-to works
|
||
sidecar = {
|
||
"bench": report["bench"],
|
||
"vllm_boot": report["vllm_boot"],
|
||
"quality": {
|
||
"total_passed": report["quality"].get("total_passed"),
|
||
"total_total": report["quality"].get("total_total"),
|
||
"total_pct": report["quality"].get("total_pct"),
|
||
"packs": report["quality"].get("packs"),
|
||
},
|
||
"aider": {
|
||
"passed_count": report["aider"].get("passed_count"),
|
||
"total_count": report["aider"].get("total_count"),
|
||
"per_language": report["aider"].get("per_language"),
|
||
},
|
||
"soak": report["soak"],
|
||
}
|
||
(tag_dir / "_internal.json").write_text(json.dumps(sidecar, indent=2))
|
||
|
||
out_path = tag_dir / "REPORT.md"
|
||
out_path.write_text(render(report))
|
||
print(f"wrote {out_path}")
|
||
|
||
if not args.no_discuss:
|
||
discuss_path = tag_dir / "REPORT-discuss.md"
|
||
discuss_path.write_text(render_discuss(report))
|
||
print(f"wrote {discuss_path}")
|
||
|
||
return 0
|
||
|
||
|
||
if __name__ == "__main__":
|
||
sys.exit(main())
|