sglang_v0.5.2/sglang/test/srt/test_multi_tokenizer.py

85 lines
2.4 KiB
Python

import unittest
from types import SimpleNamespace
import sglang.srt.managers.io_struct as io_struct
from sglang.srt.utils import kill_process_tree
from sglang.test.run_eval import run_eval
from sglang.test.test_utils import (
DEFAULT_MODEL_NAME_FOR_TEST,
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
CustomTestCase,
auto_config_device,
get_benchmark_args,
is_in_ci,
popen_launch_server,
run_benchmark,
write_github_step_summary,
)
class TestMultiTokenizer(CustomTestCase):
# from test_hicache.py
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_MODEL_NAME_FOR_TEST
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
"--tokenizer-worker-num",
8,
"--mem-fraction-static",
0.7,
],
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_mmlu(self):
args = SimpleNamespace(
base_url=self.base_url,
model=self.model,
eval_name="mmlu",
num_examples=64,
num_threads=32,
)
metrics = run_eval(args)
self.assertGreaterEqual(metrics["score"], 0.65)
def test_multi_tokenizer_ttft(self):
# from test_bench_serving.py run_bench_serving
args = get_benchmark_args(
base_url=self.base_url,
dataset_name="random",
dataset_path="",
tokenizer=None,
num_prompts=100,
random_input_len=4096,
random_output_len=2048,
sharegpt_context_len=None,
request_rate=1,
disable_stream=False,
disable_ignore_eos=False,
seed=0,
device=auto_config_device(),
lora_name=None,
)
res = run_benchmark(args)
if is_in_ci():
write_github_step_summary(
f"### test_multi_tokenizer_ttft\n"
f"median_e2e_latency_ms: {res['median_e2e_latency_ms']:.2f} ms\n"
)
self.assertLess(res["median_e2e_latency_ms"], 11000)
self.assertLess(res["median_ttft_ms"], 86)
self.assertLess(res["median_itl_ms"], 10)
if __name__ == "__main__":
unittest.main()