78 lines
2.1 KiB
Python
78 lines
2.1 KiB
Python
import time
|
|
import unittest
|
|
from types import SimpleNamespace
|
|
|
|
import requests
|
|
|
|
from sglang.srt.utils import is_cuda, kill_process_tree
|
|
from sglang.test.run_eval import run_eval
|
|
from sglang.test.test_utils import (
|
|
DEFAULT_SMALL_MOE_MODEL_NAME_FOR_TEST_BASE,
|
|
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
|
|
DEFAULT_URL_FOR_TEST,
|
|
CustomTestCase,
|
|
popen_launch_server,
|
|
)
|
|
|
|
|
|
class TestTorchCompileMoe(CustomTestCase):
|
|
@classmethod
|
|
def setUpClass(cls):
|
|
cls.model = DEFAULT_SMALL_MOE_MODEL_NAME_FOR_TEST_BASE
|
|
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=["--enable-torch-compile", "--torch-compile-max-bs", "4"],
|
|
)
|
|
|
|
@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"], 0.50)
|
|
|
|
def run_decode(self, max_new_tokens):
|
|
response = requests.post(
|
|
self.base_url + "/generate",
|
|
json={
|
|
"text": "The capital of France is",
|
|
"sampling_params": {
|
|
"temperature": 0,
|
|
"max_new_tokens": max_new_tokens,
|
|
"ignore_eos": True,
|
|
},
|
|
},
|
|
)
|
|
return response.json()
|
|
|
|
def test_throughput(self):
|
|
# Warmup
|
|
res = self.run_decode(16)
|
|
|
|
max_tokens = 256
|
|
tic = time.perf_counter()
|
|
res = self.run_decode(max_tokens)
|
|
tok = time.perf_counter()
|
|
print(f"{res=}")
|
|
throughput = max_tokens / (tok - tic)
|
|
if is_cuda():
|
|
self.assertGreaterEqual(throughput, 285)
|
|
else:
|
|
self.assertGreaterEqual(throughput, 270)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|