85 lines
2.8 KiB
Python
85 lines
2.8 KiB
Python
import unittest
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from sglang.test.ci.ci_register import register_cuda_ci
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from sglang.test.performance_test_runner import PerformanceTestParams
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from sglang.test.run_combined_tests import run_combined_tests
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from sglang.test.test_utils import ModelLaunchSettings
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# Runs on both H200 and B200 via nightly-8-gpu-common suite
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# Higher est_time due to 6 variants with both performance and accuracy tests
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register_cuda_ci(est_time=1800, suite="nightly-8-gpu-common", nightly=True)
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GPT_OSS_120B_MXFP4_MODEL_PATH = "openai/gpt-oss-120b"
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GPT_OSS_120B_EAGLE3_DRAFT_MODEL_PATH = "lmsys/EAGLE3-gpt-oss-120b-bf16"
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class TestGptOss120B(unittest.TestCase):
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"""Unified test class for GPT-OSS-120B performance and accuracy.
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Testing:
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- Basic configs for MXFP4
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- Full config for MXFP4 with reasoning-parser, tool-call-parser, and MTP
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"""
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def test_gpt_oss_120b_all_variants(self):
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"""Run performance and accuracy for all GPT-OSS-120B variants."""
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base_args = [
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"--tp=8",
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"--trust-remote-code",
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"--cuda-graph-max-bs=200",
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"--mem-fraction-static=0.93",
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]
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# Lower batch size for EAGLE3 variants to avoid OOM
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base_args_eagle3 = [
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"--tp=8",
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"--trust-remote-code",
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"--cuda-graph-max-bs=100",
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"--mem-fraction-static=0.85",
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]
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parser_args = [
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"--reasoning-parser=gpt-oss",
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"--tool-call-parser=gpt-oss",
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]
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eagle3_args = [
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"--speculative-algorithm=EAGLE3",
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f"--speculative-draft-model-path={GPT_OSS_120B_EAGLE3_DRAFT_MODEL_PATH}",
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"--speculative-num-steps=3",
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"--speculative-eagle-topk=1",
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"--speculative-num-draft-tokens=4",
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]
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eagle3_env = {
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"SGLANG_ENABLE_SPEC_V2": "1",
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"SGLANG_ALLOW_OVERWRITE_LONGER_CONTEXT_LEN": "1",
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}
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variants = [
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# Variant 1: MXFP4 baseline
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ModelLaunchSettings(
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GPT_OSS_120B_MXFP4_MODEL_PATH,
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tp_size=8,
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extra_args=base_args,
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variant="MXFP4",
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),
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# Variant 2: MXFP4 + Parsers + EAGLE3 (full featured quantized, lower batch size)
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ModelLaunchSettings(
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GPT_OSS_120B_MXFP4_MODEL_PATH,
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tp_size=8,
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extra_args=base_args_eagle3 + parser_args + eagle3_args,
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env=eagle3_env,
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variant="MXFP4+Parsers+EAGLE3",
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),
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]
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run_combined_tests(
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models=variants,
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test_name="GPT-OSS-120B",
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accuracy_params=None,
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performance_params=PerformanceTestParams(
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profile_dir="performance_profiles_gpt_oss_120b",
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),
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)
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if __name__ == "__main__":
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unittest.main()
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