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sglang/test/registered/disaggregation/test_disaggregation_aarch64.py
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Python

import os
import unittest
from types import SimpleNamespace
from sglang.test.ci.ci_register import register_cuda_ci
from sglang.test.run_eval import run_eval
from sglang.test.server_fixtures.disaggregation_fixture import (
PDDisaggregationServerBase,
)
from sglang.test.test_utils import (
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
popen_launch_pd_server,
)
QWEN3_8B_MODEL_PATH = "Qwen/Qwen3-8B"
register_cuda_ci(est_time=300, stage="base-c", runner_config="4-gpu-gb300")
class TestDisaggregationMooncakeAARCH64Accuracy(PDDisaggregationServerBase):
@classmethod
def setUpClass(cls):
super().setUpClass()
os.environ["SGLANG_MOONCAKE_CUSTOM_MEM_POOL"] = "true"
os.environ["MC_FORCE_MNNVL"] = "true"
cls.model = QWEN3_8B_MODEL_PATH
# Non blocking start servers
cls.start_prefill()
cls.start_decode()
# Block until both
cls.wait_server_ready(cls.prefill_url + "/health", process=cls.process_prefill)
cls.wait_server_ready(cls.decode_url + "/health", process=cls.process_decode)
cls.launch_lb()
@classmethod
def tearDownClass(cls):
os.environ.pop("SGLANG_MOONCAKE_CUSTOM_MEM_POOL")
os.environ.pop("MC_FORCE_MNNVL")
super().tearDownClass()
@classmethod
def start_prefill(cls):
prefill_args = [
"--trust-remote-code",
"--disaggregation-mode",
"prefill",
"--disaggregation-bootstrap-port",
cls.bootstrap_port,
"--tp",
"2",
]
prefill_args += cls.transfer_backend + cls.rdma_devices
cls.process_prefill = popen_launch_pd_server(
cls.model,
cls.prefill_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=prefill_args,
)
@classmethod
def start_decode(cls):
decode_args = [
"--trust-remote-code",
"--disaggregation-mode",
"decode",
"--disaggregation-bootstrap-port",
cls.bootstrap_port,
"--tp",
"2",
"--base-gpu-id",
"2",
]
decode_args += cls.transfer_backend + cls.rdma_devices
cls.process_decode = popen_launch_pd_server(
cls.model,
cls.decode_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=decode_args,
)
def test_gsm8k(self):
args = SimpleNamespace(
base_url=self.base_url,
model=self.model,
eval_name="gsm8k",
api="completion",
max_tokens=512,
num_examples=200,
num_threads=128,
)
metrics = run_eval(args)
print(f"Evaluation metrics: {metrics}")
self.assertGreater(metrics["score"], 0.62)
if __name__ == "__main__":
unittest.main()