59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
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_amd_ci
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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_URL_FOR_TEST,
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CustomTestCase,
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popen_launch_server,
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)
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register_amd_ci(est_time=313, suite="stage-b-test-small-1-gpu-amd")
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class TestMixtralAccuracy(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = "mistralai/Mixtral-8x7B-Instruct-v0.1"
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cls.base_url = DEFAULT_URL_FOR_TEST
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other_args = [
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"--tp",
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"2",
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"--mem-fraction-static",
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"0.9",
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"--context-length",
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"38768",
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"--quantization",
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"quark_int4fp8_moe",
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# The default aiter attention backend raises segmentation faults and other errors - as quark_int4fp8_moe is not related to attention, let's just use triton here.
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"--attention-backend",
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"triton",
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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=45 * 60,
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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=8,
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data_path=None,
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num_questions=1400,
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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"], 0.56)
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