fast (Gemma 4 26B-A4B):
- Enable mmproj GPU loading (vision ~1s, 12x faster than CPU)
- KV f16 → q8_0 (save ~2.5 GB VRAM for mmproj)
- Tensor split 0.5,0.5 → 0.43,0.57 (13/17 layers)
- Remove --mlock/--poll/--prio/-t/-tb (no measurable impact)
- measured_tps 74.65 → 71.89 (trade 3.7% speed for vision)
balanced (Qwen 3.5 35B-A3B):
- Tensor split 0.5,0.5 → 0.48,0.52 (enables pipeline parallelism)
- Ubatch 128 → 256 (prefill +78%: 649 → 1,157 t/s)
- mmproj + --no-mmproj-offload (CPU vision, VRAM headroom)
- Remove useless flags same as fast
- measured_tps 61.62 → 64.16 (+4.1%)
Other:
- Document full retuning in docs/v3_{fast,balanced}_retuning_log.md
- Session report at .planning/reports/20260411-session-report.md
- Add bench utilities: bench_short/bench_long/test_ts_ratios
- Speculative decoding (E2B draft) experimented but rejected
(+14% gen vs -31% cold start + tokenizer mismatch + mmproj conflict)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
146 lines
4.7 KiB
Python
146 lines
4.7 KiB
Python
#!/usr/bin/env python
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"""Test multiple -ts ratios to find which ones start normally (no OOM, PP enabled)."""
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import subprocess
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import time
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import json
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import urllib.request
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import urllib.error
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import sys
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import re
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from pathlib import Path
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ROOT = Path(__file__).parent.parent
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CONFIG_FILE = ROOT / "config" / "engine_models.json"
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LLAMA_LOG = ROOT / "logs" / "llama-server.log"
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ENGINE_LOG = ROOT / "logs" / "engine_test.log"
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PYTHON = r"C:\ProgramData\miniforge3\envs\variet-llm\python.exe"
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ENGINE_SCRIPT = ROOT / "engine" / "variet_engine.py"
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RATIOS = [
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("0.5", "0.5"),
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("0.48", "0.52"),
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("0.47", "0.53"),
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("0.45", "0.55"),
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("0.43", "0.57"),
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("0.40", "0.60"),
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]
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try:
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sys.stdout.reconfigure(encoding="utf-8")
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except Exception:
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pass
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def kill_servers():
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subprocess.run(
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["powershell", "-Command",
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"Get-WmiObject Win32_Process | Where-Object { $_.CommandLine -like '*engine/variet_engine.py*' -or $_.Name -eq 'llama-server.exe' } | ForEach-Object { Stop-Process -Id $_.ProcessId -Force -ErrorAction SilentlyContinue }"],
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capture_output=True
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)
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time.sleep(2)
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def update_config(ts_a, ts_b):
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with open(CONFIG_FILE, encoding="utf-8") as f:
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cfg = json.load(f)
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args = cfg["roles"]["balanced"]["args"]
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for i, a in enumerate(args):
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if a == "-ts" and i + 1 < len(args):
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args[i + 1] = f"{ts_a},{ts_b}"
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break
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with open(CONFIG_FILE, "w", encoding="utf-8") as f:
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json.dump(cfg, f, indent=2, ensure_ascii=False)
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def start_engine():
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LLAMA_LOG.write_text("")
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ENGINE_LOG.write_text("")
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return subprocess.Popen(
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[PYTHON, str(ENGINE_SCRIPT)],
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cwd=str(ROOT),
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stdout=open(ENGINE_LOG, "wb"),
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stderr=subprocess.STDOUT,
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creationflags=subprocess.CREATE_NEW_PROCESS_GROUP
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)
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def wait_for_result(timeout=180):
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"""Return (status, log_tail) where status is 'ready'|'oom'|'error'|'timeout'."""
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deadline = time.time() + timeout
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while time.time() < deadline:
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time.sleep(3)
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# check engine status
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try:
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with urllib.request.urlopen("http://localhost:8000/engine/status", timeout=2) as r:
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data = json.loads(r.read())
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if data.get("state") == "ready":
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return "ready", ""
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if data.get("state") == "error":
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return "error", ""
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except Exception:
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pass
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return "timeout", ""
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def analyze_log():
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if not LLAMA_LOG.exists():
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return {}
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text = LLAMA_LOG.read_text(encoding="utf-8", errors="ignore")
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result = {
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"pp_enabled": "pipeline parallelism enabled" in text,
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"pp_fallback": "retrying without pipeline parallelism" in text,
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"oom": "out of memory" in text,
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"listening": "main: server is listening" in text,
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}
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m = re.search(r"CUDA0 model buffer size = +([0-9.]+) MiB", text)
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if m:
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result["cuda0_model"] = float(m.group(1))
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m = re.search(r"CUDA1 model buffer size = +([0-9.]+) MiB", text)
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if m:
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result["cuda1_model"] = float(m.group(1))
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m = re.search(r"CUDA0 KV buffer size = +([0-9.]+) MiB", text)
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if m:
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result["cuda0_kv"] = float(m.group(1))
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m = re.search(r"CUDA1 KV buffer size = +([0-9.]+) MiB", text)
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if m:
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result["cuda1_kv"] = float(m.group(1))
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m = re.search(r"CUDA0 compute buffer size = +([0-9.]+) MiB", text)
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if m:
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result["cuda0_compute"] = float(m.group(1))
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m = re.search(r"CUDA1 compute buffer size = +([0-9.]+) MiB", text)
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if m:
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result["cuda1_compute"] = float(m.group(1))
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return result
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def main():
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results = []
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print(f"{'ratio':<14} {'status':<10} {'PP':<6} {'cuda0_m':<9} {'cuda1_m':<9} {'cuda0_kv':<9} {'cuda1_kv':<9} {'c0_comp':<9} {'c1_comp':<9}")
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print("-" * 110)
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for ts_a, ts_b in RATIOS:
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label = f"{ts_a},{ts_b}"
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kill_servers()
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update_config(ts_a, ts_b)
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proc = start_engine()
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status, _ = wait_for_result(timeout=180)
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info = analyze_log()
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pp = "ON" if info.get("pp_enabled") and not info.get("pp_fallback") else ("FALLBACK" if info.get("pp_fallback") else "?")
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c0m = f"{info.get('cuda0_model', 0):.0f}"
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c1m = f"{info.get('cuda1_model', 0):.0f}"
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c0kv = f"{info.get('cuda0_kv', 0):.0f}"
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c1kv = f"{info.get('cuda1_kv', 0):.0f}"
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c0c = f"{info.get('cuda0_compute', 0):.0f}"
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c1c = f"{info.get('cuda1_compute', 0):.0f}"
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print(f"{label:<14} {status:<10} {pp:<6} {c0m:<9} {c1m:<9} {c0kv:<9} {c1kv:<9} {c0c:<9} {c1c:<9}")
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results.append({"ratio": label, "status": status, "info": info})
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proc.terminate()
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time.sleep(1)
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kill_servers()
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print("\nDone.")
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if __name__ == "__main__":
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main()
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