165 lines
4.7 KiB
Python
165 lines
4.7 KiB
Python
import os
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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_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_DEEPSEEK_NVFP4_MODEL_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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try_cached_model,
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)
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register_cuda_ci(est_time=1800, suite="stage-c-test-4-gpu-gb200")
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class TestDeepseekR1Nvfp4CuteDSLDeepEP(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = try_cached_model(DEFAULT_DEEPSEEK_NVFP4_MODEL_FOR_TEST)
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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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"--mem-fraction-static",
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"0.8",
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"--max-prefill-tokens",
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"16384",
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"--max-running-requests",
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"256",
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"--chunked-prefill-size",
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"1024",
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"--tp",
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"4",
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"--dp",
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"4",
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"--ep",
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"4",
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"--moe-dense-tp-size",
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"1",
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"--enable-dp-attention",
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"--quantization",
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"modelopt_fp4",
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"--attention-backend",
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"trtllm_mla",
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"--moe-a2a-backend",
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"deepep",
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"--moe-runner-backend",
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"flashinfer_cutedsl",
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"--deepep-mode",
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"low_latency",
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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=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=other_args,
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env={
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**os.environ,
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"SGLANG_DEEPEP_BF16_DISPATCH": "1",
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"SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK": "256",
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"SGLANG_MOE_NVFP4_DISPATCH": "0",
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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_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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class TestDummyWithSBO(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = try_cached_model(DEFAULT_DEEPSEEK_NVFP4_MODEL_FOR_TEST)
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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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"--mem-fraction-static",
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"0.05",
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"--max-prefill-tokens",
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"16384",
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"--max-running-requests",
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"256",
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"--chunked-prefill-size",
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"1024",
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"--cuda-graph-bs",
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"64",
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"--tp",
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"4",
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"--dp",
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"4",
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"--ep",
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"4",
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"--moe-dense-tp-size",
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"1",
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"--enable-dp-attention",
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"--quantization",
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"modelopt_fp4",
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"--attention-backend",
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"trtllm_mla",
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"--moe-a2a-backend",
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"deepep",
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"--moe-runner-backend",
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"flashinfer_cutedsl",
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"--deepep-mode",
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"low_latency",
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"--json-model-override-args",
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'{"num_hidden_layers": 1, "first_k_dense_replace": 0, "n_routed_experts": 24}',
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"--enable-single-batch-overlap",
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"--load-format",
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"dummy",
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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=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=other_args,
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env={
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**os.environ,
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"SGLANG_DEEPEP_BF16_DISPATCH": "1",
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"SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK": "256",
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"SGLANG_MOE_NVFP4_DISPATCH": "0",
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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_gsm8k(self):
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args = SimpleNamespace(
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num_shots=0,
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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=16,
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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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if __name__ == "__main__":
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unittest.main()
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