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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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.test_utils import (
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DEFAULT_URL_FOR_TEST,
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CustomTestCase,
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popen_launch_server,
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try_cached_model,
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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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FULL_DEEPSEEK_V3_MODEL_PATH = "deepseek-ai/DeepSeek-V3-0324"
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SERVER_LAUNCH_TIMEOUT = 1000
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class TestDeepseekR1Fp8Flashinfer(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = try_cached_model(FULL_DEEPSEEK_V3_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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"--disable-radix-cache",
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"--max-running-requests",
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"512",
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"--chunked-prefill-size",
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"8192",
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"--mem-fraction-static",
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"0.9",
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"--cuda-graph-max-bs",
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"128",
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"--max-prefill-tokens",
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"8192",
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"--kv-cache-dtype",
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"fp8_e4m3",
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"--quantization",
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"fp8",
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"--tensor-parallel-size",
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"8",
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"--data-parallel-size",
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"1",
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"--expert-parallel-size",
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"1",
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"--scheduler-recv-interval",
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"10",
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"--stream-interval",
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"10",
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"--attention-backend",
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"trtllm_mla",
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"--fp8-gemm-backend",
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"flashinfer_trtllm",
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"--moe-runner-backend",
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"flashinfer_trtllm",
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"--enable-symm-mem",
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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_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=512,
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parallel=512,
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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"Eval accuracy of GSM8K: {metrics=}")
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self.assertGreater(metrics["accuracy"], 0.92)
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if __name__ == "__main__":
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unittest.main()
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