ci: migrate MLA tests to test/registered/mla/ (#15798)
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import unittest
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from types import SimpleNamespace
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from sglang.srt.utils import kill_process_tree
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from sglang.test.ci.ci_register import register_amd_ci, register_cuda_ci
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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_MLA_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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# MLA attention test with MGSM evaluation
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register_cuda_ci(est_time=194, suite="stage-b-test-small-1-gpu")
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register_amd_ci(
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est_time=242,
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suite="stage-a-test-1",
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disabled="see https://github.com/sgl-project/sglang/issues/13107",
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)
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class TestMLA(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = DEFAULT_MLA_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=[
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"--trust-remote-code",
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"--enable-torch-compile",
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"--torch-compile-max-bs",
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"4",
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"--chunked-prefill-size",
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"256",
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],
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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_mgsm_en(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="mgsm_en",
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num_examples=None,
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num_threads=1024,
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)
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metrics = run_eval(args)
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self.assertGreater(metrics["score"], 0.8)
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if __name__ == "__main__":
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unittest.main()
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