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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

144 行
4.4 KiB
Python

"""
python3 -m unittest test_encoder_attention_backend.py
"""
import json
import os
import unittest
from pathlib import Path
import requests
from sglang.srt.utils import kill_process_tree
from sglang.srt.utils.hf_transformers import get_tokenizer
from sglang.test.ci.ci_register import register_xpu_ci
from sglang.test.test_utils import (
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
CustomTestCase,
popen_launch_server,
)
register_xpu_ci(est_time=360, suite="stage-b-test-1-gpu-xpu")
class TestEncoderAttention(CustomTestCase):
# Test "xpu_attn" attention backend
@classmethod
def setUpClass(cls):
cls.model = "Qwen/Qwen3-VL-2B-Thinking"
cls.tokenizer = get_tokenizer(cls.model)
cls.base_url = DEFAULT_URL_FOR_TEST
cls.image_path = str(
(Path(__file__).resolve().parents[3] / "examples/assets/example_image.png")
)
if not os.path.exists(cls.image_path):
raise FileNotFoundError(f"Image not found: {cls.image_path}")
cls.common_args = [
"--device",
"xpu",
"--mm-attention-backend",
"xpu_attn",
]
os.environ["SGLANG_USE_SGL_XPU"] = "1"
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
*cls.common_args,
],
)
@classmethod
def tearDownClass(cls):
"""Fixture that is run once after all tests in the class."""
if hasattr(cls, "process") and cls.process:
cls.process.terminate()
try:
cls.process.wait(timeout=30)
except Exception:
# Force kill if it didn't exit cleanly in time
kill_process_tree(cls.process.pid)
def get_request_json(self, max_new_tokens=32, n=1):
response = requests.post(
self.base_url + "/generate",
json={
"text": "<image>\n Tell me what you can see from the image.",
"image_data": self.image_path,
"sampling_params": {
"temperature": 0 if n == 1 else 1.0,
"max_new_tokens": max_new_tokens,
},
},
)
return response.json()
def run_decode(
self,
max_new_tokens=128,
n=1,
):
ret = self.get_request_json(max_new_tokens=max_new_tokens, n=n)
print(json.dumps(ret, indent=2))
def assert_one_item(item):
if item["meta_info"]["finish_reason"]["type"] == "stop":
self.assertEqual(
item["meta_info"]["finish_reason"]["matched"],
self.tokenizer.eos_token_id,
)
elif item["meta_info"]["finish_reason"]["type"] == "length":
self.assertEqual(
len(item["output_ids"]), item["meta_info"]["completion_tokens"]
)
self.assertEqual(len(item["output_ids"]), max_new_tokens)
# Determine whether to assert a single item or multiple items based on n
if n == 1:
assert_one_item(ret)
else:
self.assertEqual(len(ret), n)
for i in range(n):
assert_one_item(ret[i])
print("=" * 100)
def test_run(self):
self.run_decode()
class TestEncoderAttention_Triton(TestEncoderAttention):
# Test "triton_attn" attention backend
@classmethod
def setUpClass(cls):
cls.model = "Qwen/Qwen3-VL-2B-Thinking"
cls.tokenizer = get_tokenizer(cls.model)
cls.base_url = DEFAULT_URL_FOR_TEST
cls.image_path = str(
(Path(__file__).resolve().parents[3] / "examples/assets/example_image.png")
)
if not os.path.exists(cls.image_path):
raise FileNotFoundError(f"Image not found: {cls.image_path}")
cls.common_args = [
"--device",
"xpu",
"--mm-attention-backend",
"triton_attn",
]
os.environ["SGLANG_USE_SGL_XPU"] = "0"
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
*cls.common_args,
],
)
if __name__ == "__main__":
unittest.main()