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[Test] Add basic matched stop for beta eagle (#11833)

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This commit is contained in:
Liangsheng Yin
2025-10-20 01:17:00 +08:00
committed by GitHub
parent 48738af7f9
commit 7a020e0f3b
4 changed files with 201 additions and 222 deletions
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157
python/sglang/test/kit_matched_stop.py Normal file
View File

@@ -0,0 +1,157 @@
import json
import requests
MANY_NEW_TOKENS_PROMPT = """
Please write an extremely detailed and vivid fantasy story, set in a world full of intricate magic systems, political intrigue, and complex characters.
Ensure that you thoroughly describe every scene, character's motivations, and the environment. Include long, engaging dialogues and elaborate on the inner thoughts of the characters.
Each section should be as comprehensive as possible to create a rich and immersive experience for the reader.
The story should span multiple events, challenges, and character developments over time. Aim to make the story at least 3,000 words long.
"""
class MatchedStopMixin:
def _run_completions_generation(
self,
prompt=MANY_NEW_TOKENS_PROMPT,
max_tokens=1,
stop=None,
stop_regex=None,
finish_reason=None,
matched_stop=None,
):
payload = {
"prompt": prompt,
"model": self.model,
"temperature": 0,
"top_p": 1,
"max_tokens": max_tokens,
}
if stop is not None:
payload["stop"] = stop
if stop_regex is not None:
payload["stop_regex"] = stop_regex
response_completions = requests.post(
self.base_url + "/v1/completions",
json=payload,
)
res = response_completions.json()
print(json.dumps(res))
print("=" * 100)
if not isinstance(matched_stop, list):
matched_stop = [matched_stop]
assert (
res["choices"][0]["finish_reason"] == finish_reason
), f"Expected finish_reason: {finish_reason}, but got: {res['choices'][0]['finish_reason']}"
assert (
res["choices"][0]["matched_stop"] in matched_stop
), f"Expected matched_stop: {matched_stop}, but got: {res['choices'][0]['matched_stop']}"
def _run_chat_completions_generation(
self,
prompt=MANY_NEW_TOKENS_PROMPT,
max_tokens=1,
stop=None,
stop_regex=None,
finish_reason=None,
matched_stop=None,
):
chat_payload = {
"model": self.model,
"messages": [
{"role": "system", "content": "You are a helpful AI assistant"},
{"role": "user", "content": prompt},
],
"temperature": 0,
"top_p": 1,
"max_tokens": max_tokens,
}
if stop is not None:
chat_payload["stop"] = stop
if stop_regex is not None:
chat_payload["stop_regex"] = stop_regex
response_chat = requests.post(
self.base_url + "/v1/chat/completions",
json=chat_payload,
)
res = response_chat.json()
print(json.dumps(res))
print("=" * 100)
if not isinstance(matched_stop, list):
matched_stop = [matched_stop]
assert (
res["choices"][0]["finish_reason"] == finish_reason
), f"Expected finish_reason: {finish_reason}, but got: {res['choices'][0]['finish_reason']}"
assert (
res["choices"][0]["matched_stop"] in matched_stop
), f"Expected matched_stop: {matched_stop}, but got: {res['choices'][0]['matched_stop']}"
def test_finish_stop_str(self):
self._run_completions_generation(
max_tokens=1000, stop="\n", finish_reason="stop", matched_stop="\n"
)
self._run_chat_completions_generation(
max_tokens=1000, stop="\n", finish_reason="stop", matched_stop="\n"
)
def test_finish_stop_regex_str(self):
STOP_REGEX_STR = r"and|or"
self._run_completions_generation(
max_tokens=1000,
stop_regex=STOP_REGEX_STR,
finish_reason="stop",
matched_stop=STOP_REGEX_STR,
)
self._run_chat_completions_generation(
max_tokens=1000,
stop_regex=STOP_REGEX_STR,
finish_reason="stop",
matched_stop=STOP_REGEX_STR,
)
# Match a complete sentence
STOP_REGEX_STR_SENTENCE = r"[.!?]\s*$"
self._run_chat_completions_generation(
max_tokens=1000,
stop_regex=STOP_REGEX_STR_SENTENCE,
finish_reason="stop",
matched_stop=STOP_REGEX_STR_SENTENCE,
)
def test_finish_stop_eos(self):
llama_format_prompt = """\
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
You are a helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|>
What is 2 + 2?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
"""
eos_token_ids = [128000, 128009, 2]
self._run_completions_generation(
prompt=llama_format_prompt,
max_tokens=1000,
finish_reason="stop",
matched_stop=eos_token_ids,
)
self._run_chat_completions_generation(
prompt="What is 2 + 2?",
max_tokens=1000,
finish_reason="stop",
matched_stop=eos_token_ids,
)
def test_finish_length(self):
self._run_completions_generation(
max_tokens=5, finish_reason="length", matched_stop=None
)
self._run_chat_completions_generation(
max_tokens=5, finish_reason="length", matched_stop=None
)

3
python/sglang/test/test_utils.py
View File

@@ -1622,6 +1622,9 @@ class CustomTestCase(unittest.TestCase):
max_retry=max_retry,
)
def setUp(self):
print(f"[Test Method] {self._testMethodName}", flush=True)
def dump_bench_raw_result(
path: str,

145
test/srt/openai_server/validation/test_matched_stop.py
View File

@@ -1,10 +1,8 @@
import json
import unittest
import requests
from sglang.srt.sampling.sampling_params import MAX_LEN, get_max_seq_length
from sglang.srt.utils import kill_process_tree
from sglang.test.kit_matched_stop import MatchedStopMixin
from sglang.test.test_utils import (
DEFAULT_MODEL_NAME_FOR_TEST,
DEFAULT_URL_FOR_TEST,
@@ -12,15 +10,8 @@ from sglang.test.test_utils import (
popen_launch_server,
)
MANY_NEW_TOKENS_PROMPT = """
Please write an extremely detailed and vivid fantasy story, set in a world full of intricate magic systems, political intrigue, and complex characters.
Ensure that you thoroughly describe every scene, character's motivations, and the environment. Include long, engaging dialogues and elaborate on the inner thoughts of the characters.
Each section should be as comprehensive as possible to create a rich and immersive experience for the reader.
The story should span multiple events, challenges, and character developments over time. Aim to make the story at least 3,000 words long.
"""
class TestMatchedStop(CustomTestCase):
class TestMatchedStop(CustomTestCase, MatchedStopMixin):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_MODEL_NAME_FOR_TEST
@@ -36,138 +27,6 @@ class TestMatchedStop(CustomTestCase):
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def run_completions_generation(
self,
prompt=MANY_NEW_TOKENS_PROMPT,
max_tokens=1,
stop=None,
stop_regex=None,
finish_reason=None,
matched_stop=None,
):
payload = {
"prompt": prompt,
"model": self.model,
"temperature": 0,
"top_p": 1,
"max_tokens": max_tokens,
}
if stop is not None:
payload["stop"] = stop
if stop_regex is not None:
payload["stop_regex"] = stop_regex
response_completions = requests.post(
self.base_url + "/v1/completions",
json=payload,
)
print(json.dumps(response_completions.json()))
print("=" * 100)
assert (
response_completions.json()["choices"][0]["finish_reason"] == finish_reason
)
assert response_completions.json()["choices"][0]["matched_stop"] == matched_stop
def run_chat_completions_generation(
self,
prompt=MANY_NEW_TOKENS_PROMPT,
max_tokens=1,
stop=None,
stop_regex=None,
finish_reason=None,
matched_stop=None,
):
chat_payload = {
"model": self.model,
"messages": [
{"role": "system", "content": "You are a helpful AI assistant"},
{"role": "user", "content": prompt},
],
"temperature": 0,
"top_p": 1,
"max_tokens": max_tokens,
}
if stop is not None:
chat_payload["stop"] = stop
if stop_regex is not None:
chat_payload["stop_regex"] = stop_regex
response_chat = requests.post(
self.base_url + "/v1/chat/completions",
json=chat_payload,
)
print(json.dumps(response_chat.json()))
print("=" * 100)
assert response_chat.json()["choices"][0]["finish_reason"] == finish_reason
assert response_chat.json()["choices"][0]["matched_stop"] == matched_stop
def test_finish_stop_str(self):
self.run_completions_generation(
max_tokens=1000, stop="\n", finish_reason="stop", matched_stop="\n"
)
self.run_chat_completions_generation(
max_tokens=1000, stop="\n", finish_reason="stop", matched_stop="\n"
)
def test_finish_stop_regex_str(self):
STOP_REGEX_STR = r"and|or"
self.run_completions_generation(
max_tokens=1000,
stop_regex=STOP_REGEX_STR,
finish_reason="stop",
matched_stop=STOP_REGEX_STR,
)
self.run_chat_completions_generation(
max_tokens=1000,
stop_regex=STOP_REGEX_STR,
finish_reason="stop",
matched_stop=STOP_REGEX_STR,
)
# Match a complete sentence
STOP_REGEX_STR_SENTENCE = r"[.!?]\s*$"
self.run_chat_completions_generation(
max_tokens=1000,
stop_regex=STOP_REGEX_STR_SENTENCE,
finish_reason="stop",
matched_stop=STOP_REGEX_STR_SENTENCE,
)
def test_finish_stop_eos(self):
llama_format_prompt = """
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
You are a helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|>
What is 2 + 2?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
"""
eos_token_id = 128009
self.run_completions_generation(
prompt=llama_format_prompt,
max_tokens=1000,
finish_reason="stop",
matched_stop=eos_token_id,
)
self.run_chat_completions_generation(
prompt="What is 2 + 2?",
max_tokens=1000,
finish_reason="stop",
matched_stop=eos_token_id,
)
def test_finish_length(self):
self.run_completions_generation(
max_tokens=5, finish_reason="length", matched_stop=None
)
self.run_chat_completions_generation(
max_tokens=5, finish_reason="length", matched_stop=None
)
class TestRegexPatternMaxLength(unittest.TestCase):
@classmethod

118
test/srt/test_eagle_infer_beta.py
View File

@@ -3,7 +3,10 @@ from types import SimpleNamespace
from sglang.srt.utils import kill_process_tree
from sglang.test.few_shot_gsm8k import run_eval
from sglang.test.kit_matched_stop import MatchedStopMixin
from sglang.test.test_utils import (
DEFAULT_EAGLE_DRAFT_MODEL_FOR_TEST,
DEFAULT_EAGLE_TARGET_MODEL_FOR_TEST,
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
CustomTestCase,
@@ -11,93 +14,50 @@ from sglang.test.test_utils import (
)
class TestEagleBS1(CustomTestCase):
num_questions = 60
@classmethod
def setUpClass(cls):
cls.model = "meta-llama/Llama-2-7b-chat-hf"
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",
"--attention-backend",
"triton",
"--enable-beta-spec",
"--speculative-algorithm",
"EAGLE",
"--speculative-draft-model",
"lmzheng/sglang-EAGLE-llama2-chat-7B",
"--speculative-num-steps",
"5",
"--speculative-eagle-topk",
"1",
"--speculative-num-draft-tokens",
"6",
"--max-running-requests",
"1",
],
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_gsm8k(self):
args = SimpleNamespace(
num_shots=5,
data_path=None,
num_questions=self.num_questions,
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"TestEagleBS1 -- {metrics=}")
self.assertGreater(
metrics["accuracy"], 0.33
) # 0.3333 for 60 questions; 0.234 for 1319 questions
class TestEagleLargeBS(CustomTestCase):
num_questions = 10000
class TestEagleServerBase(CustomTestCase, MatchedStopMixin):
max_running_requests = 64
other_args = [
"--trust-remote-code",
"--attention-backend",
"triton",
"--enable-beta-spec",
"--speculative-algorithm",
"EAGLE",
"--speculative-draft-model",
"lmzheng/sglang-EAGLE-llama2-chat-7B",
"--speculative-num-steps",
"5",
"--speculative-eagle-topk",
"1",
"--speculative-num-draft-tokens",
"6",
"--mem-fraction-static",
"0.75",
"--max-running-requests",
str(max_running_requests),
"--cuda-graph-bs",
*[str(i) for i in range(1, max_running_requests + 1)],
]
attention_backend = "triton"
spec_steps = 5
spec_topk = 1
spec_draft_tokens = 6
page_size = 1
other_launch_args = []
model = DEFAULT_EAGLE_TARGET_MODEL_FOR_TEST
draft_model = DEFAULT_EAGLE_DRAFT_MODEL_FOR_TEST
@classmethod
def setUpClass(cls):
cls.model = "meta-llama/Llama-2-7b-chat-hf"
cls.base_url = DEFAULT_URL_FOR_TEST
launch_args = [
"--enable-beta-spec",
"--trust-remote-code",
"--attention-backend",
cls.attention_backend,
"--speculative-algorithm",
"EAGLE",
"--speculative-draft-model",
cls.draft_model,
"--speculative-num-steps",
cls.spec_steps,
"--speculative-eagle-topk",
cls.spec_topk,
"--speculative-num-draft-tokens",
cls.spec_draft_tokens,
"--page-size",
str(cls.page_size),
"--mem-fraction-static",
"0.75",
"--max-running-requests",
str(cls.max_running_requests),
"--cuda-graph-bs",
*[str(i) for i in range(1, cls.max_running_requests + 1)],
]
launch_args.extend(cls.other_launch_args)
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=cls.other_args,
other_args=launch_args,
)
@classmethod
@@ -108,7 +68,7 @@ class TestEagleLargeBS(CustomTestCase):
args = SimpleNamespace(
num_shots=5,
data_path=None,
num_questions=self.num_questions,
num_questions=1000,
max_new_tokens=512,
parallel=128,
host="http://127.0.0.1",