150 lines
4.9 KiB
Python
150 lines
4.9 KiB
Python
"""Beam width sweep benchmark: 100 concurrent ShareGPT prompts
|
|
(prompt_len < 100), max_new_tokens=10, widths 10/50/100/200/400.
|
|
Primary metric is aggregate beam tok/s.
|
|
|
|
Manual test (GPU host): python3 test_beam_search_perf_sweep.py
|
|
"""
|
|
|
|
import asyncio
|
|
import os
|
|
import time
|
|
import unittest
|
|
|
|
import aiohttp
|
|
|
|
from sglang.benchmark.datasets.sharegpt import sample_sharegpt_requests
|
|
from sglang.srt.utils import kill_process_tree
|
|
from sglang.srt.utils.hf_transformers_utils import get_tokenizer
|
|
from sglang.test.test_utils import (
|
|
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
|
|
DEFAULT_URL_FOR_TEST,
|
|
CustomTestCase,
|
|
popen_launch_server,
|
|
)
|
|
|
|
BEAM_WIDTHS = [10, 50, 100, 200, 400]
|
|
NUM_PROMPTS = 100
|
|
MAX_PROMPT_LEN = 100
|
|
MAX_NEW_TOKENS = 10
|
|
CLIENT_TIMEOUT_S = 1200
|
|
|
|
|
|
async def _generate(session, base_url, prompt, width):
|
|
start = time.perf_counter()
|
|
async with session.post(
|
|
f"{base_url}/generate",
|
|
json={
|
|
"text": prompt,
|
|
"sampling_params": {"beam_width": width, "max_new_tokens": MAX_NEW_TOKENS},
|
|
},
|
|
) as resp:
|
|
payload = await resp.json()
|
|
latency = time.perf_counter() - start
|
|
beam_results = payload.get("meta_info", {}).get("beam_results") or []
|
|
return resp.status, len(beam_results), latency
|
|
|
|
|
|
class _BeamSweepBase(CustomTestCase):
|
|
# Primary metric is aggregate beam tok/s (reqs x width x new_tokens /
|
|
# elapsed); QPS is secondary since it conflates width.
|
|
|
|
extra_server_args = []
|
|
pool_label = "default pool"
|
|
|
|
@classmethod
|
|
def setUpClass(cls):
|
|
cls.model = os.environ.get("SGLANG_TEST_BEAM_MODEL", "Qwen/Qwen3-1.7B")
|
|
cls.base_url = DEFAULT_URL_FOR_TEST
|
|
cls.process = popen_launch_server(
|
|
cls.model,
|
|
cls.base_url,
|
|
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
|
|
# 0.7 leaves headroom for the full-vocab [num_beam_rows, vocab]
|
|
# logprobs tensor, which OOMs at large width x concurrency.
|
|
other_args=["--disable-overlap-schedule", "--mem-fraction-static", "0.7"]
|
|
+ cls.extra_server_args,
|
|
)
|
|
|
|
tokenizer = get_tokenizer(cls.model)
|
|
rows = sample_sharegpt_requests(
|
|
dataset_path="", num_requests=4000, tokenizer=tokenizer
|
|
)
|
|
cls.prompts = [r.prompt for r in rows if r.prompt_len < MAX_PROMPT_LEN][
|
|
:NUM_PROMPTS
|
|
]
|
|
assert len(cls.prompts) == NUM_PROMPTS, (
|
|
f"only {len(cls.prompts)} short prompts sampled"
|
|
)
|
|
|
|
@classmethod
|
|
def tearDownClass(cls):
|
|
kill_process_tree(cls.process.pid)
|
|
|
|
async def _run_one_width(self, width):
|
|
timeout = aiohttp.ClientTimeout(total=CLIENT_TIMEOUT_S)
|
|
async with aiohttp.ClientSession(timeout=timeout) as session:
|
|
start = time.perf_counter()
|
|
results = await asyncio.gather(
|
|
*[
|
|
_generate(session, self.base_url, prompt, width)
|
|
for prompt in self.prompts
|
|
]
|
|
)
|
|
elapsed = time.perf_counter() - start
|
|
return results, elapsed
|
|
|
|
def _run_sweep(self):
|
|
report = []
|
|
for width in BEAM_WIDTHS:
|
|
results, elapsed = asyncio.run(self._run_one_width(width))
|
|
|
|
num_ok = sum(1 for status, _, _ in results if status == 200)
|
|
self.assertEqual(
|
|
num_ok, NUM_PROMPTS, f"width={width}: {NUM_PROMPTS - num_ok} failed"
|
|
)
|
|
for status, num_beams, _ in results:
|
|
self.assertGreaterEqual(num_beams, 1)
|
|
self.assertLessEqual(num_beams, width)
|
|
|
|
beam_tok_s = NUM_PROMPTS * width * MAX_NEW_TOKENS / elapsed
|
|
qps = NUM_PROMPTS / elapsed
|
|
report.append((width, beam_tok_s, qps, elapsed))
|
|
print(
|
|
f"width={width:4d} beam_tok/s={beam_tok_s:9.0f} "
|
|
f"qps={qps:6.2f} elapsed={elapsed:6.2f}s"
|
|
)
|
|
|
|
print(f"\nBeam width sweep ({self.pool_label}):")
|
|
print("| beam width | beam tok/s | qps | elapsed (s) |")
|
|
print("|---|---|---|---|")
|
|
for width, beam_tok_s, qps, elapsed in report:
|
|
print(f"| {width} | {beam_tok_s:.0f} | {qps:.2f} | {elapsed:.2f} |")
|
|
|
|
|
|
class TestBeamSweepDefaultPool(_BeamSweepBase):
|
|
"""Default req-slot pool (4096): beam rows pin at ~4000 for width >= 50, so
|
|
this curve saturates at the pool, not the engine."""
|
|
|
|
def test_beam_width_sweep(self):
|
|
self._run_sweep()
|
|
|
|
|
|
class TestBeamSweepLargePool(_BeamSweepBase):
|
|
"""Enlarged pool (16384) for the engine ceiling: ~40 width-400 groups run
|
|
concurrently, affordable because --context-length is short."""
|
|
|
|
extra_server_args = [
|
|
"--max-running-requests",
|
|
"16384",
|
|
"--context-length",
|
|
"2048",
|
|
]
|
|
pool_label = "large pool (16384 slots)"
|
|
|
|
def test_beam_width_sweep(self):
|
|
self._run_sweep()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|