Files
sglang/test/registered/ep/test_flashinfer_a2a.py
T

201 lines
5.9 KiB
Python

import unittest
from types import SimpleNamespace
import requests
from sglang.srt.utils import kill_process_tree
from sglang.test.ci.ci_register import register_cuda_ci
from sglang.test.run_eval import run_eval
from sglang.test.test_utils import (
DEFAULT_PORT_FOR_SRT_TEST_RUNNER,
DEFAULT_URL_FOR_TEST,
CustomTestCase,
popen_launch_server,
)
register_cuda_ci(est_time=561, stage="base-c", runner_config="4-gpu-gb300")
# Keep rendezvous ports below the ephemeral range on the 4-GPU GB300 runner.
NCCL_PORT_BASE = DEFAULT_PORT_FOR_SRT_TEST_RUNNER + 110
DEEPSEEK_V3_FP4_MODEL = "nvidia/DeepSeek-V3-0324-FP4"
GLM52_NVFP4_MODEL = "nvidia/GLM-5.2-NVFP4"
QWEN3_FP8_MODEL = "Qwen/Qwen3-Next-80B-A3B-Instruct-FP8"
SERVER_LAUNCH_TIMEOUT = 1000
FLASHINFER_A2A_ENV = {
"SGLANG_FLASHINFER_NUM_MAX_DISPATCH_TOKENS_PER_RANK": "4096",
}
class TestFlashinferA2ATrtllmRoutedFP4(CustomTestCase):
"""flashinfer A2A + flashinfer_trtllm_routed with modelopt_fp4 (DeepSeek V3)."""
@classmethod
def setUpClass(cls):
cls.model = DEEPSEEK_V3_FP4_MODEL
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=SERVER_LAUNCH_TIMEOUT,
other_args=[
"--tp",
"4",
"--ep",
"4",
"--dp",
"4",
"--enable-dp-attention",
"--nccl-port",
str(NCCL_PORT_BASE),
"--moe-a2a-backend",
"flashinfer",
"--moe-runner-backend",
"flashinfer_trtllm_routed",
"--quantization",
"modelopt_fp4",
"--disable-flashinfer-autotune",
"--model-loader-extra-config",
'{"enable_multithread_load": true}',
],
)
@classmethod
def tearDownClass(cls):
if hasattr(cls, "process") and cls.process:
kill_process_tree(cls.process.pid)
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"{metrics=}")
self.assertGreater(metrics["score"], 0.90)
class TestFlashinferA2ACutedslStaticFP4(CustomTestCase):
"""flashinfer A2A + static EP + flashinfer_cutedsl with GLM-5.2 NVFP4."""
@classmethod
def setUpClass(cls):
cls.model = GLM52_NVFP4_MODEL
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=SERVER_LAUNCH_TIMEOUT,
other_args=[
"--tp",
"4",
"--ep",
"4",
"--dp",
"4",
"--enable-dp-attention",
"--nccl-port",
str(NCCL_PORT_BASE + 1),
"--moe-a2a-backend",
"flashinfer",
"--moe-runner-backend",
"flashinfer_cutedsl",
"--ep-dispatch-algorithm",
"static",
"--quantization",
"modelopt_fp4",
"--trust-remote-code",
"--chunked-prefill-size",
"4096",
"--mem-fraction-static",
"0.78",
"--cuda-graph-max-bs-decode",
"16",
"--disable-flashinfer-autotune",
"--model-loader-extra-config",
'{"enable_multithread_load": true}',
],
env=FLASHINFER_A2A_ENV,
)
@classmethod
def tearDownClass(cls):
if hasattr(cls, "process") and cls.process:
kill_process_tree(cls.process.pid)
def test_generate(self):
response = requests.post(
self.base_url + "/generate",
json={
"text": "What is 2 + 2?",
"sampling_params": {"temperature": 0, "max_new_tokens": 8},
},
timeout=120,
)
self.assertEqual(response.status_code, 200, response.text)
self.assertTrue(response.json()["text"])
class TestFlashinferA2ATrtllmRoutedFP8(CustomTestCase):
"""flashinfer A2A + flashinfer_trtllm_routed with fp8 (Qwen3-Next)."""
@classmethod
def setUpClass(cls):
cls.model = QWEN3_FP8_MODEL
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=SERVER_LAUNCH_TIMEOUT,
other_args=[
"--tp",
"4",
"--ep",
"4",
"--dp",
"4",
"--enable-dp-attention",
"--nccl-port",
str(NCCL_PORT_BASE + 2),
"--moe-a2a-backend",
"flashinfer",
"--moe-runner-backend",
"flashinfer_trtllm_routed",
"--attention-backend",
"triton",
"--mem-fraction-static",
"0.7",
"--mamba-ssm-dtype",
"bfloat16",
"--disable-flashinfer-autotune",
],
)
@classmethod
def tearDownClass(cls):
if hasattr(cls, "process") and cls.process:
kill_process_tree(cls.process.pid)
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"{metrics=}")
self.assertGreater(metrics["score"], 0.93)
if __name__ == "__main__":
unittest.main()