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Add pytorch sampling backend ut (#1425)
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import unittest | ||
from types import SimpleNamespace | ||
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from sglang.srt.utils import kill_child_process | ||
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, | ||
popen_launch_server, | ||
) | ||
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class TestPyTorchSamplingBackend(unittest.TestCase): | ||
@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=["--sampling-backend", "pytorch"], | ||
) | ||
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@classmethod | ||
def tearDownClass(cls): | ||
kill_child_process(cls.process.pid) | ||
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def test_mmlu(self): | ||
args = SimpleNamespace( | ||
base_url=self.base_url, | ||
model=self.model, | ||
eval_name="mmlu", | ||
num_examples=64, | ||
num_threads=32, | ||
) | ||
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metrics = run_eval(args) | ||
assert metrics["score"] >= 0.65 | ||
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if __name__ == "__main__": | ||
unittest.main() |