Files
sglang/test/srt/test_int4fp8_moe.py
fxmarty-amd 5af84c8af5 [AMD][Quantization] Add int4fp8_moe online quantization on ROCm (#7392)
Co-authored-by: Dehua Tang <dehtang@amd.com>
Co-authored-by: HAI <hixiao@gmail.com>
Co-authored-by: YC Tseng <yctseng@amd.com>
2026-01-14 01:44:40 -08:00

56 lines
1.5 KiB
Python

from types import SimpleNamespace
from sglang.srt.utils import kill_process_tree
from sglang.test.few_shot_gsm8k import run_eval
from sglang.test.test_utils import (
DEFAULT_URL_FOR_TEST,
CustomTestCase,
popen_launch_server,
)
class TestMixtralAccuracy(CustomTestCase):
@classmethod
def setUpClass(cls):
cls.model = "mistralai/Mixtral-8x7B-Instruct-v0.1"
cls.base_url = DEFAULT_URL_FOR_TEST
other_args = [
"--tp",
"2",
"--mem-fraction-static",
"0.9",
"--context-length",
"38768",
"--quantization",
"quark_int4fp8_moe",
# The default aiter attention backend raises segmentation faults and other errors - as quark_int4fp8_moe is not related to attention, let's just use triton here.
"--attention-backend",
"triton",
]
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=45 * 60,
other_args=other_args,
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
num_shots=8,
data_path=None,
num_questions=1400,
max_new_tokens=512,
parallel=128,
host="http://127.0.0.1",
port=int(self.base_url.split(":")[-1]),
)
metrics = run_eval(args)
print(f"{metrics=}")
self.assertGreater(metrics["accuracy"], 0.56)