91 lines
2.5 KiB
Python
91 lines
2.5 KiB
Python
import unittest
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from types import SimpleNamespace
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import requests
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from sglang.srt.utils import kill_process_tree
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from sglang.test.run_eval import run_eval
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from sglang.test.test_utils import (
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DEFAULT_MODEL_NAME_FOR_TEST,
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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DEFAULT_URL_FOR_TEST,
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CustomTestCase,
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popen_launch_server,
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)
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class TestPyTorchSamplingBackend(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = DEFAULT_MODEL_NAME_FOR_TEST
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cls.base_url = DEFAULT_URL_FOR_TEST
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cls.process = popen_launch_server(
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cls.model,
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cls.base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=["--sampling-backend", "pytorch", "--disable-radix-cache"],
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)
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@classmethod
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def tearDownClass(cls):
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kill_process_tree(cls.process.pid)
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def test_mmlu(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="mmlu",
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num_examples=64,
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num_threads=32,
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temperature=0.1,
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)
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metrics = run_eval(args)
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self.assertGreaterEqual(metrics["score"], 0.65)
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def test_greedy(self):
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first_text = None
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# ensure the answer is identical across single response
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for _ in range(5):
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response_single = requests.post(
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self.base_url + "/generate",
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json={
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"text": "The capital of Germany is",
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"sampling_params": {
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"temperature": 0,
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"max_new_tokens": 32,
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},
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},
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).json()
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text = response_single["text"]
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if first_text is None:
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first_text = text
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self.assertEqual(text, first_text)
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first_text = None
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response_batch = requests.post(
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self.base_url + "/generate",
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json={
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"text": ["The capital of Germany is"] * 10,
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"sampling_params": {
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"temperature": 0,
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"max_new_tokens": 32,
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},
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},
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).json()
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# ensure the answer is identical among the batch
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for i in range(10):
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text = response_batch[i]["text"]
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if first_text is None:
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first_text = text
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self.assertEqual(text, first_text)
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if __name__ == "__main__":
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unittest.main()
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