103 lines
3.0 KiB
Python
103 lines
3.0 KiB
Python
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_cuda_ci
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from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
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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_URL_FOR_TEST,
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CustomTestCase,
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is_in_ci,
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popen_launch_server,
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try_cached_model,
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write_github_step_summary,
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)
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register_cuda_ci(est_time=3600, suite="nightly-8-gpu-b200", nightly=True)
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# Use the latest version of DeepSeek-V3.2
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DEEPSEEK_V32_MODEL_PATH = "deepseek-ai/DeepSeek-V3.2"
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SERVER_LAUNCH_TIMEOUT = 1200
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class TestDeepseekV32Accuracy(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = try_cached_model(DEEPSEEK_V32_MODEL_PATH)
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cls.base_url = DEFAULT_URL_FOR_TEST
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other_args = [
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"--trust-remote-code",
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"--tp",
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"8",
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"--enable-dp-attention",
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"--dp",
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"8",
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"--tool-call-parser",
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"deepseekv32",
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"--reasoning-parser",
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"deepseek-v3",
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"--model-loader-extra-config",
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'{"enable_multithread_load": true,"num_threads": 64}',
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]
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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=SERVER_LAUNCH_TIMEOUT,
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other_args=other_args,
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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_a_gsm8k(
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self,
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):
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args = SimpleNamespace(
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num_shots=20,
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data_path=None,
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num_questions=1400,
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parallel=1400,
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max_new_tokens=512,
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host="http://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_few_shot_gsm8k(args)
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print(f"{metrics=}")
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if is_in_ci():
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write_github_step_summary(
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f"### test_gsm8k (deepseek-v32)\n" f'{metrics["accuracy"]=:.3f}\n'
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)
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self.assertGreater(metrics["accuracy"], 0.935)
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def test_gpqa(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=DEEPSEEK_V32_MODEL_PATH,
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eval_name="gpqa",
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num_examples=198,
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# use enough threads to allow parallelism
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num_threads=198,
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max_tokens=120000,
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thinking_mode="deepseek-v3",
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temperature=0.1,
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# Repeat 4 times for shorter runtime. Ideally we should repeat at least 8 times.
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repeat=4,
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)
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print(f"Evaluation start for gpqa")
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metrics = run_eval(args)
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print(f"Evaluation end for gpqa: {metrics=}, expected_score=0.835")
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mean_score = metrics["mean_score"]
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self.assertGreaterEqual(mean_score, 0.835)
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if is_in_ci():
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write_github_step_summary(
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f"### test_gpqa (deepseek-v32)\n" f"Mean Score: {mean_score:.3f}\n"
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)
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if __name__ == "__main__":
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unittest.main()
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