Files
sglang/test/srt/test_ascend_mla_backend.py
ronnie_zheng 1e0e549766 Ascend attention backend(PA&MLA) (#7722)
Co-authored-by: Maksim <makcum888e@mail.ru>
Co-authored-by: VDV1985 <vladdv85@mail.ru>
2025-07-03 09:23:19 -07:00

97 lines
2.8 KiB
Python

"""
Usage:
python3 -m unittest test_ascend_mla_backend.TestAscendMLABackend.test_gsm8k
"""
import os
import unittest
from types import SimpleNamespace
from urllib.parse import urlparse
from sglang.srt.utils import kill_process_tree
from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
from sglang.test.run_eval import run_eval
from sglang.test.test_utils import (
DEFAULT_MLA_MODEL_NAME_FOR_TEST,
DEFAULT_MODEL_NAME_FOR_TEST,
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
CustomTestCase,
is_in_ci,
popen_launch_server,
run_bench_offline_throughput,
)
if "ASCEND_RT_VISIBLE_DEVICES" not in os.environ:
os.environ["ASCEND_RT_VISIBLE_DEVICES"] = "0,1,2,3"
DEFAULT_PORT_FOR_SRT_TEST_RUNNER = (
7000 + int(os.environ.get("ASCEND_RT_VISIBLE_DEVICES", "0")[0]) * 100
)
DEFAULT_URL_FOR_TEST = f"http://127.0.0.1:{DEFAULT_PORT_FOR_SRT_TEST_RUNNER + 1000}"
DEFAULT_MODEL_NAME_FOR_TEST = "/models/DeepSeek-V2-Lite-Chat"
if not os.path.exists(DEFAULT_MODEL_NAME_FOR_TEST):
DEFAULT_MODEL_NAME_FOR_TEST = DEFAULT_MLA_MODEL_NAME_FOR_TEST
class TestAscendMLABackend(CustomTestCase):
def test_latency(self):
output_throughput = run_bench_offline_throughput(
DEFAULT_MODEL_NAME_FOR_TEST,
[
"--attention-backend",
"ascend",
"--mem-fraction-static",
0.7,
"--tp-size",
"4",
"--trust-remote-code",
"--disable-cuda-graph",
],
)
print(f"{output_throughput=}")
if is_in_ci():
self.assertGreater(output_throughput, 18)
def test_gsm8k(self):
model = DEFAULT_MODEL_NAME_FOR_TEST
base_url = DEFAULT_URL_FOR_TEST
url = urlparse(base_url)
process = popen_launch_server(
model,
base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
"--attention-backend",
"ascend",
"--mem-fraction-static",
0.7,
"--tp-size",
"4",
"--trust-remote-code",
"--disable-cuda-graph",
],
)
try:
args = SimpleNamespace(
num_shots=5,
data_path=None,
num_questions=128,
max_new_tokens=512,
parallel=128,
host=f"http://{url.hostname}",
port=int(url.port),
)
metrics = run_eval_few_shot_gsm8k(args)
self.assertGreaterEqual(metrics["accuracy"], 0.62)
self.assertGreaterEqual(metrics["output_throughput"], 50)
finally:
kill_process_tree(process.pid)
if __name__ == "__main__":
unittest.main()