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51 行
1.5 KiB
Python
51 行
1.5 KiB
Python
import unittest
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import sglang as sgl
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from sglang.srt.utils.common import temp_set_env
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from sglang.test.ci.ci_register import register_cuda_ci
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from sglang.test.test_utils import CustomTestCase
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register_cuda_ci(est_time=380, suite="nightly-1-gpu", nightly=True)
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TEST_GCS_MODEL = "gs://vertex-model-garden-public-us/codegemma/codegemma-2b/"
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PROMPTS = [
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"Hello, my name is",
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"The president of the United States is",
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"The capital of France is",
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"The future of AI is",
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]
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class TestRunaiModelLoader(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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with temp_set_env(
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GOOGLE_CLOUD_PROJECT="fake-project",
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RUNAI_STREAMER_GCS_USE_ANONYMOUS_CREDENTIALS="true",
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CLOUD_STORAGE_EMULATOR_ENDPOINT="https://storage.googleapis.com",
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):
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cls.engine = sgl.Engine(
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model_path=TEST_GCS_MODEL,
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load_format="runai_streamer",
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cuda_graph_max_bs_decode=1,
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max_total_tokens=64,
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)
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@classmethod
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def tearDownClass(cls):
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if hasattr(cls, "engine") and cls.engine:
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cls.engine.shutdown()
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def test_generate_produces_output(self):
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outputs = self.engine.generate(PROMPTS)
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self.assertEqual(len(outputs), len(PROMPTS))
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for i, output in enumerate(outputs):
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text = output["text"]
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self.assertIsInstance(text, str)
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self.assertGreater(len(text), 0, f"Prompt {i} produced empty output")
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if __name__ == "__main__":
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unittest.main()
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