ci: migrate 2-GPU tests to test/registered/ (#16529)
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@@ -1,46 +0,0 @@
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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.few_shot_gsm8k import run_eval
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from sglang.test.test_utils import (
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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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)
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class TestKimiLinear(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = "moonshotai/Kimi-Linear-48B-A3B-Instruct"
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cls.base_url = DEFAULT_URL_FOR_TEST
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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=["--tp-size", "2", "--trust-remote"],
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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=200,
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max_new_tokens=512,
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parallel=128,
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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(args)
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print(f"{metrics=}")
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self.assertGreater(metrics["accuracy"], 0.88)
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if __name__ == "__main__":
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unittest.main()
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@@ -1,96 +0,0 @@
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import unittest
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from sglang.srt.utils import is_blackwell
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from sglang.test.kits.gsm8k_accuracy_kit import GSM8KMixin
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from sglang.test.server_fixtures.default_fixture import DefaultServerBase
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class TestNvidiaNemotronNanoV2BF16(GSM8KMixin, DefaultServerBase):
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model = "nvidia/NVIDIA-Nemotron-Nano-9B-v2"
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gsm8k_accuracy_thres = 0.87
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other_args = ["--max-mamba-cache-size", "256"]
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class TestNvidiaNemotronNanoV2BF16PP(GSM8KMixin, DefaultServerBase):
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model = "nvidia/NVIDIA-Nemotron-Nano-9B-v2"
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gsm8k_accuracy_thres = 0.87
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other_args = ["--max-mamba-cache-size", "256", "--pp-size", "2"]
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class TestNvidiaNemotronNanoV2FP8(GSM8KMixin, DefaultServerBase):
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gsm8k_accuracy_thres = 0.87
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model = "nvidia/NVIDIA-Nemotron-Nano-9B-v2-FP8"
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other_args = ["--max-mamba-cache-size", "256"]
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@unittest.skipIf(not is_blackwell(), "NVFP4 only supported on blackwell")
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class TestNvidiaNemotronNanoV2NVFP4(GSM8KMixin, DefaultServerBase):
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gsm8k_accuracy_thres = 0.855
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model = "nvidia/NVIDIA-Nemotron-Nano-9B-v2-NVFP4"
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other_args = ["--max-mamba-cache-size", "256"]
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@unittest.skip(
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"STANDALONE speculative decoding does not yet support target and draft models "
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"with different hidden sizes (Nemotron-9B: 4480, Llama-3.2-1B: 2048)"
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)
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class TestNvidiaNemotronNanoV2SpeculativeDecoding(GSM8KMixin, DefaultServerBase):
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gsm8k_accuracy_thres = 0.87
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model = "nvidia/NVIDIA-Nemotron-Nano-9B-v2"
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other_args = [
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"--speculative-algorithm",
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"STANDALONE",
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"--speculative-num-steps",
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"2",
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"--speculative-eagle-topk",
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"3",
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"--speculative-num-draft-tokens",
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"5",
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"--speculative-draft-model-path",
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"meta-llama/Llama-3.2-1B",
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"--speculative-draft-load-format",
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"dummy",
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"--max-running-requests",
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"8",
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"--max-total-tokens",
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"2048",
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"--json-model-override-args",
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'{"vocab_size": 131072}',
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]
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@unittest.skip(
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"STANDALONE speculative decoding does not yet support target and draft models "
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"with different hidden sizes (Nemotron-9B: 4480, Llama-3.2-1B: 2048)"
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)
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class TestNvidiaNemotronNanoV2SpeculativeDecodingBF16Cache(
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GSM8KMixin, DefaultServerBase
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):
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gsm8k_accuracy_thres = 0.87
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model = "nvidia/NVIDIA-Nemotron-Nano-9B-v2"
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other_args = [
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"--speculative-algorithm",
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"STANDALONE",
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"--speculative-num-steps",
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"2",
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"--speculative-eagle-topk",
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"3",
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"--speculative-num-draft-tokens",
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"5",
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"--speculative-draft-model-path",
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"meta-llama/Llama-3.2-1B",
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"--speculative-draft-load-format",
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"dummy",
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"--max-running-requests",
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"8",
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"--max-total-tokens",
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"2048",
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"--json-model-override-args",
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'{"vocab_size": 131072}',
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"--mamba-ssm-dtype",
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"bfloat16",
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]
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if __name__ == "__main__":
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unittest.main()
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