44 lines
1.2 KiB
Python
44 lines
1.2 KiB
Python
"""A small end-to-end eval coverage for the transformers modeling backend."""
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import unittest
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from types import SimpleNamespace
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from sglang.test.ci.ci_register import register_cuda_ci
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from sglang.test.few_shot_gsm8k import run_eval
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from sglang.test.server_fixtures.default_fixture import DefaultServerBase
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register_cuda_ci(est_time=180, suite="stage-b-test-small-1-gpu")
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class TestTransformersBackendEval(DefaultServerBase):
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model = "HuggingFaceTB/SmolLM3-3B"
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gsm8k_num_questions = 30
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gsm8k_accuracy_thres = 0.5
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gsm8k_parallel = 30
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other_args = [
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"--model-impl",
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"transformers",
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"--enable-torch-compile",
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"--torch-compile-max-bs",
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"4",
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"--disable-cuda-graph",
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]
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def test_gsm8k(self):
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args = SimpleNamespace(
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num_shots=5,
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data_path=None,
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num_questions=self.gsm8k_num_questions,
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max_new_tokens=512,
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parallel=self.gsm8k_parallel,
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host="127.0.0.1",
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port=int(self.base_url.split(":")[-1]),
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)
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metrics = run_eval(args)
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print(f"{metrics=}")
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self.assertGreaterEqual(metrics["accuracy"], self.gsm8k_accuracy_thres)
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if __name__ == "__main__":
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unittest.main()
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