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sgl-project--sglang/test/manual/test_wave_attention_backend.py
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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

62 lines
1.5 KiB
Python

"""
Usage:
python3 -m unittest test_wave_attention_backend.TestWaveAttnBackend.test_mmlu
"""
import unittest
from types import SimpleNamespace
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,
is_in_ci,
popen_launch_server,
run_bench_one_batch,
)
class TestWaveAttnBackend(unittest.TestCase):
def test_latency(self):
_, output_throughput, _ = run_bench_one_batch(
DEFAULT_MODEL_NAME_FOR_TEST,
[
"--attention-backend",
"wave",
"--enable-torch-compile",
],
)
if is_in_ci():
self.assertGreater(output_throughput, 153)
def _test_mmlu(self):
model = DEFAULT_MODEL_NAME_FOR_TEST
base_url = DEFAULT_URL_FOR_TEST
process = popen_launch_server(
model,
base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=["--attention-backend", "wave"],
)
try:
args = SimpleNamespace(
base_url=base_url,
model=model,
eval_name="mmlu",
num_examples=64,
num_threads=32,
)
metrics = run_eval(args)
self.assertGreaterEqual(metrics["score"], 0.65)
finally:
kill_process_tree(process.pid)
if __name__ == "__main__":
unittest.main()