File size: 3,347 Bytes
de561c0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 | #!/usr/bin/env python3
"""Measure TTFT and TPOT by streaming from llama-server."""
import argparse
import json
import subprocess
import sys
import time
import requests
SERVER_BIN = "./build/bin/llama-server"
PORT = 8081
PROMPT = "Explain the difference between machine learning and deep learning in detail." * 8 # ~512 tokens
MAX_TOKENS = 128
RUNS = 3
def wait_for_server(address, timeout=120):
for _ in range(timeout):
try:
r = requests.get(f"{address}/health", timeout=2)
if r.status_code == 200:
return True
except Exception:
pass
time.sleep(1)
return False
def measure_once(address):
payload = {
"messages": [{"role": "user", "content": PROMPT}],
"max_tokens": MAX_TOKENS,
"stream": True,
"temperature": 0.0,
}
t0 = time.perf_counter()
ttft = None
n_tokens = 0
with requests.post(f"{address}/v1/chat/completions", json=payload, stream=True, timeout=120) as resp:
for line in resp.iter_lines():
if not line:
continue
line = line.decode("utf-8")
if not line.startswith("data:"):
continue
data = line[5:].strip()
if data == "[DONE]":
break
try:
chunk = json.loads(data)
delta = chunk["choices"][0]["delta"].get("content", "")
if delta:
if ttft is None:
ttft = time.perf_counter() - t0
n_tokens += 1
except Exception:
continue
t_total = time.perf_counter() - t0
tpot = (t_total - ttft) / max(n_tokens - 1, 1) if n_tokens > 1 else 0
return ttft, tpot, n_tokens, t_total
def main():
parser = argparse.ArgumentParser()
parser.add_argument("-m", "--model", required=True)
parser.add_argument("--runs", type=int, default=RUNS)
parser.add_argument("--device", default=None,
help="GGML device string, e.g. CUDA0 (default: all GPUs)")
args = parser.parse_args()
address = f"http://127.0.0.1:{PORT}"
cmd = [SERVER_BIN, "-m", args.model, "-ngl", "99", "--port", str(PORT), "--log-disable"]
if args.device:
cmd += ["-dev", args.device]
print(f"Starting server: {' '.join(cmd)}", file=sys.stderr)
proc = subprocess.Popen(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
try:
if not wait_for_server(address):
print("ERROR: server did not start", file=sys.stderr)
proc.kill()
sys.exit(1)
print("Server ready", file=sys.stderr)
ttfts, tpots = [], []
for i in range(args.runs):
ttft, tpot, n_tokens, t_total = measure_once(address)
ttfts.append(ttft * 1000)
tpots.append(tpot * 1000)
print(f" Run {i+1}: TTFT={ttft*1000:.1f}ms TPOT={tpot*1000:.1f}ms tokens={n_tokens}", file=sys.stderr)
avg_ttft = sum(ttfts) / len(ttfts)
avg_tpot = sum(tpots) / len(tpots)
result = {"ttft_ms": round(avg_ttft, 1), "tpot_ms": round(avg_tpot, 1), "latency_ms": round(avg_ttft + avg_tpot, 1)}
print(json.dumps(result))
finally:
proc.kill()
proc.wait()
if __name__ == "__main__":
main()
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