154 lines
4.3 KiB
Python
154 lines
4.3 KiB
Python
"""
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Usage:
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python3 test/srt/test_flashmla.py
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"""
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import unittest
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from types import SimpleNamespace
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import requests
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import torch
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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.test_utils import (
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DEFAULT_MODEL_NAME_FOR_TEST_MLA,
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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_ci,
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popen_launch_server,
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run_bench_one_batch,
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)
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class TestFlashMLAAttnBackend(unittest.TestCase):
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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 = ["--trust-remote-code"]
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if torch.cuda.is_available() and torch.version.cuda:
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other_args.extend(
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[
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"--enable-torch-compile",
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"--cuda-graph-max-bs",
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"2",
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"--attention-backend",
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"flashmla",
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]
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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=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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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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class TestFlashMLAAttnLatency(unittest.TestCase):
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def test_latency(self):
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output_throughput = run_bench_one_batch(
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DEFAULT_MODEL_NAME_FOR_TEST_MLA,
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[
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"--attention-backend",
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"flashmla",
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"--enable-torch-compile",
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"--cuda-graph-max-bs",
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"16",
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"--trust-remote-code",
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],
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)
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if is_in_ci():
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self.assertGreater(output_throughput, 100)
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class TestFlashMLAMTP(CustomTestCase):
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@classmethod
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def setUpClass(cls):
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cls.model = "lmsys/sglang-ci-dsv3-test"
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cls.base_url = DEFAULT_URL_FOR_TEST
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other_args = ["--trust-remote-code"]
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if torch.cuda.is_available() and torch.version.cuda:
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other_args.extend(
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[
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"--cuda-graph-max-bs",
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"4",
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"--disable-radix",
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"--enable-torch-compile",
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"--torch-compile-max-bs",
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"1",
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"--speculative-algorithm",
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"EAGLE",
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"--speculative-draft",
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"lmsys/sglang-ci-dsv3-test-NextN",
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"--speculative-num-steps",
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"1",
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"--speculative-eagle-topk",
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"1",
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"--speculative-num-draft-tokens",
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"2",
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"--attention-backend",
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"flashmla",
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]
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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=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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print(f"{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(f"{avg_spec_accept_length=}")
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self.assertGreater(avg_spec_accept_length, 1.8)
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if __name__ == "__main__":
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unittest.main()
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