sglang_v0.5.2/sglang/test/srt/test_two_batch_overlap.py

153 lines
4.8 KiB
Python

import os
import unittest
from types import SimpleNamespace
import requests
from sglang.srt.model_executor.forward_batch_info import ForwardMode
from sglang.srt.two_batch_overlap import (
compute_split_seq_index,
compute_split_token_index,
)
from sglang.srt.utils import kill_process_tree
from sglang.test.run_eval import run_eval
from sglang.test.test_utils import (
DEFAULT_ENABLE_THINKING_MODEL_NAME_FOR_TEST,
DEFAULT_MLA_MODEL_NAME_FOR_TEST,
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
popen_launch_server,
)
class TestTwoBatchOverlap(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_MLA_MODEL_NAME_FOR_TEST
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=[
"--trust-remote-code",
"--tp",
"2",
"--dp",
"2",
"--enable-dp-attention",
"--moe-a2a-backend",
"deepep",
"--deepep-mode",
"normal",
"--disable-cuda-graph", # DeepEP normal does not support CUDA Graph
"--enable-two-batch-overlap",
],
env={"SGL_ENABLE_JIT_DEEPGEMM": "0", **os.environ},
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_generate_single_prompt(self):
response = requests.post(
self.base_url + "/generate",
# we use an uncommon start to minimise the chance that the cache is hit by chance
json={
"text": "_ 1+1=2, 1+2=3, 1+3=4, 1+4=",
"sampling_params": {"temperature": 0, "max_new_tokens": 8},
},
)
print(f"{response.json()=}")
self.assertEqual(response.json()["text"], "5, 1+5=6")
def test_mmlu(self):
args = SimpleNamespace(
base_url=self.base_url,
model=self.model,
eval_name="mmlu",
num_examples=64,
num_threads=32,
)
metrics = run_eval(args)
self.assertGreater(metrics["score"], 0.5)
class TestTwoBatchOverlapUnitTest(unittest.TestCase):
def test_compute_split_seq_and_token_index(self):
for num_tokens, expect in [
(0, 0),
(100, 50),
(99, 49),
]:
actual = compute_split_seq_index(
forward_mode=ForwardMode.DECODE,
num_tokens=num_tokens,
extend_lens=None,
token_num_per_seq=1,
)
self.assertEqual(actual, expect)
for extend_lens, expect in [
([], (0, 0)),
([42], (0, 21)),
([42, 999], (1, 520)),
([999, 42], (0, 520)),
([498, 502], (1, 498)),
([4096, 4096, 4096, 4096], (2, 8192)),
([4095, 4096, 4096, 4096, 1], (2, 8191)),
([1, 4095, 4096, 4096, 4096], (3, 8192)),
([4097, 4096, 4096, 4095, 1], (2, 8193)),
([1, 1, 1, 1, 99999], (4, 50001)),
([99999, 1, 1, 1, 1], (0, 50001)),
]:
actual_seq_idx = compute_split_seq_index(
forward_mode=ForwardMode.EXTEND,
num_tokens=None,
extend_lens=extend_lens,
token_num_per_seq=None,
)
actual_token_idx = compute_split_token_index(
split_seq_index=actual_seq_idx,
forward_mode=ForwardMode.EXTEND,
extend_seq_lens=extend_lens,
token_num_per_seq=None,
)
actual = (actual_seq_idx, actual_token_idx)
print(f"{extend_lens=} {expect=} {actual=}")
self.assertEqual(actual, expect)
class TestQwen3TwoBatchOverlap(TestTwoBatchOverlap):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_ENABLE_THINKING_MODEL_NAME_FOR_TEST
cls.base_url = DEFAULT_URL_FOR_TEST
cls.api_key = "sk-1234"
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=[
"--trust-remote-code",
"--tp",
"2",
"--dp",
"2",
"--enable-dp-attention",
"--moe-a2a-backend",
"deepep",
"--deepep-mode",
"normal",
"--disable-cuda-graph", # DeepEP normal does not support CUDA Graph
"--enable-two-batch-overlap",
],
env={"SGL_ENABLE_JIT_DEEPGEMM": "0", **os.environ},
)
if __name__ == "__main__":
unittest.main()