73 lines
1.9 KiB
Python
73 lines
1.9 KiB
Python
import os
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import unittest
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from types import SimpleNamespace
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import requests
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from sglang.srt.utils import get_device_sm, kill_process_tree
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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_MODEL_NAME_FOR_TEST_LOCAL_ATTENTION,
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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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@unittest.skipIf(get_device_sm() < 90, "Test requires CUDA SM 90 or higher")
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class TestFlashAttention3LocalAttn(CustomTestCase):
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model = DEFAULT_MODEL_NAME_FOR_TEST_LOCAL_ATTENTION
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base_url = DEFAULT_URL_FOR_TEST
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accuracy_threshold = 0.90
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@classmethod
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def get_server_args(cls):
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return [
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"--cuda-graph-max-bs",
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"2",
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"--attention-backend",
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"fa3",
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"--tp",
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"4",
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"--context-length",
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"1000000",
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]
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@classmethod
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def setUpClass(cls):
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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=cls.get_server_args(),
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env=os.environ,
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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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requests.get(self.base_url + "/flush_cache")
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args = SimpleNamespace(
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num_shots=4,
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num_questions=100,
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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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data_path=None,
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)
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metrics = run_eval_few_shot_gsm8k(args)
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print(f"{metrics=}")
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# Use the appropriate metric key based on the test class
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metric_key = "accuracy"
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self.assertGreater(metrics[metric_key], self.accuracy_threshold)
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if __name__ == "__main__":
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unittest.main()
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