171 lines
4.7 KiB
Python
171 lines
4.7 KiB
Python
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 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.run_eval import run_eval
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from sglang.test.test_utils import (
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DEFAULT_MLA_MODEL_NAME_FOR_TEST,
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DEFAULT_MODEL_NAME_FOR_TEST_MLA,
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DEFAULT_MODEL_NAME_FOR_TEST_MLA_NEXTN,
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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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is_in_amd_ci,
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popen_launch_server,
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)
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class TestDPAttentionDP2TP2(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = DEFAULT_MLA_MODEL_NAME_FOR_TEST
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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=[
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"--trust-remote-code",
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"--tp",
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"2",
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"--enable-dp-attention",
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"--dp",
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"2",
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"--enable-torch-compile",
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"--torch-compile-max-bs",
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"2",
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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_mgsm_en(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="mgsm_en",
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num_examples=None,
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num_threads=1024,
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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["score"], 0.8)
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class TestDPAttentionDP2TP2DeepseekV3MTP(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = DEFAULT_MODEL_NAME_FOR_TEST_MLA
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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",
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"--speculative-algorithm",
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"EAGLE",
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"--speculative-num-steps",
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"2",
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"--speculative-eagle-topk",
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"4",
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"--speculative-num-draft-tokens",
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"4",
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"--speculative-draft-model-path",
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DEFAULT_MODEL_NAME_FOR_TEST_MLA_NEXTN,
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"--tp-size",
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"2",
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"--enable-dp-attention",
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"--dp-size",
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"2",
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]
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if not is_in_amd_ci():
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other_args += ["--mem-frac", "0.7"]
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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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)
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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=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_few_shot_gsm8k(args)
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print(metrics)
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self.assertGreater(metrics["accuracy"], 0.60)
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server_info = requests.get(self.base_url + "/get_server_info")
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avg_spec_accept_length = server_info.json()["internal_states"][0][
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"avg_spec_accept_length"
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]
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print(
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f"###test_gsm8k (deepseek-v3 mtp + dp):\n"
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f"accuracy={metrics['accuracy']=:.3f}\n"
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f"{avg_spec_accept_length=:.3f}\n"
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)
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self.assertGreater(avg_spec_accept_length, 2.5)
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class TestDPAttentionMinimumTokenLoadBalance(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = DEFAULT_MLA_MODEL_NAME_FOR_TEST
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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=[
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"--trust-remote-code",
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"--tp",
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"2",
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"--enable-dp-attention",
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"--dp",
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"2",
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"--enable-torch-compile",
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"--torch-compile-max-bs",
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"2",
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"--load-balance-method",
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"minimum_tokens",
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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_mgsm_en(self):
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args = SimpleNamespace(
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base_url=self.base_url,
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model=self.model,
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eval_name="mgsm_en",
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num_examples=None,
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num_threads=1024,
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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["score"], 0.8)
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if __name__ == "__main__":
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unittest.main()
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