Files
sglang/test/registered/4-gpu-models/test_qwen3_next_models.py

131 lines
4.0 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.few_shot_gsm8k import run_eval
from sglang.test.kl_test_utils import (
test_input_output_logprobs_match_decode_cache_hit_helper,
test_input_output_logprobs_match_prefill_cache_hit_helper,
)
from sglang.test.test_utils import (
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
CustomTestCase,
popen_launch_server,
)
register_cuda_ci(est_time=350, suite="stage-c-test-4-gpu-h100")
QWEN3_NEXT_MODEL = "Qwen/Qwen3-Next-80B-A3B-Instruct"
ACC_THRESHOLDS = {
QWEN3_NEXT_MODEL: {"kl_div": 0.0025, "gsm8k": 0.93},
}
def send_request_helper(base_url: str, text: str):
response = requests.post(
base_url + "/generate",
json={
"text": text,
"sampling_params": {
"max_new_tokens": 1,
},
},
)
return response.json()
class TestQwen3Next(CustomTestCase):
@classmethod
def setUpClass(cls):
cls.model = QWEN3_NEXT_MODEL
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
"--tp-size",
"4",
"--chunked-prefill-size",
"2048",
"--mamba-scheduler-strategy",
"extra_buffer",
"--mamba-track-interval",
"128",
],
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
num_shots=5,
data_path=None,
num_questions=200,
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.assertGreaterEqual(
metrics["accuracy"], ACC_THRESHOLDS[self.model]["gsm8k"]
)
def test_input_output_logprobs_match_prefill_cache_hit(self):
test_input_output_logprobs_match_prefill_cache_hit_helper(
self.base_url,
ACC_THRESHOLDS,
self.model,
max_samples=32,
max_new_tokens=512,
)
def test_input_output_logprobs_match_decode_cache_hit(self):
test_input_output_logprobs_match_decode_cache_hit_helper(
self.base_url,
ACC_THRESHOLDS,
self.model,
max_samples=32,
max_new_tokens=512,
)
def test_prefix_cache_branching(self):
print("running test_prefix_cache_branching")
requests.get(self.base_url + "/flush_cache")
branching_pos = 257
text_prefix = "hi" * branching_pos
suffix_list = ["this" * 256, "here" * 256, "that" * 256]
cache_hit_list = [False, False, True]
# First request only prefill the entire sequence
# Second request won't have cache hit, but will cache the branching point
# Third request will have cache hit on the branching point
for i, (suffix, cache_hit) in enumerate(
zip(suffix_list, cache_hit_list, strict=True)
):
result = send_request_helper(self.base_url, text_prefix + suffix)
cached_tokens = result["meta_info"]["cached_tokens"]
if cache_hit:
expected_cached_tokens = branching_pos // 64 * 64
assert (
cached_tokens == expected_cached_tokens
), f"{i=}, {cache_hit=}, {cached_tokens=} is not equal to {expected_cached_tokens=}, {branching_pos=}"
else:
assert (
cached_tokens == 0
), f"{i=}, {cache_hit=}, {cached_tokens=} is not 0"
print("test_prefix_cache_branching passed")
if __name__ == "__main__":
unittest.main()