Files
sglang/test/srt/test_skip_tokenizer_init.py
Lianmin Zheng ac2387279e Support penalty in overlap mode; return logprob with chunked prefill; improve benchmark scripts (#3988)
Co-authored-by: SangBin Cho <rkooo567@gmail.com>
Co-authored-by: dhou-xai <dhou@x.ai>
Co-authored-by: Hanming Lu <hanming_lu@berkeley.edu>
2025-03-03 00:12:04 -08:00

181 lines
6.0 KiB
Python

"""
python3 -m unittest test_skip_tokenizer_init.TestSkipTokenizerInit.test_parallel_sample
python3 -m unittest test_skip_tokenizer_init.TestSkipTokenizerInit.run_decode_stream
"""
import json
import unittest
import requests
from transformers import AutoTokenizer
from sglang.srt.utils import kill_process_tree
from sglang.test.test_utils import (
DEFAULT_SMALL_MODEL_NAME_FOR_TEST,
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
popen_launch_server,
)
class TestSkipTokenizerInit(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_SMALL_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=["--skip-tokenizer-init", "--stream-output"],
)
cls.tokenizer = AutoTokenizer.from_pretrained(
DEFAULT_SMALL_MODEL_NAME_FOR_TEST, use_fast=False
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def run_decode(
self,
prompt_text="The capital of France is",
max_new_tokens=32,
return_logprob=False,
top_logprobs_num=0,
n=1,
):
input_ids = self.tokenizer(prompt_text, return_tensors="pt")["input_ids"][
0
].tolist()
response = requests.post(
self.base_url + "/generate",
json={
"input_ids": input_ids,
"sampling_params": {
"temperature": 0 if n == 1 else 0.5,
"max_new_tokens": max_new_tokens,
"n": n,
"stop_token_ids": [self.tokenizer.eos_token_id],
},
"stream": False,
"return_logprob": return_logprob,
"top_logprobs_num": top_logprobs_num,
"logprob_start_len": 0,
},
)
ret = response.json()
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)
self.assertEqual(item["meta_info"]["prompt_tokens"], len(input_ids))
if return_logprob:
self.assertEqual(
len(item["meta_info"]["input_token_logprobs"]),
len(input_ids),
f'{len(item["meta_info"]["input_token_logprobs"])} mismatch with {len(input_ids)}',
)
self.assertEqual(
len(item["meta_info"]["output_token_logprobs"]),
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 run_decode_stream(self, return_logprob=False, top_logprobs_num=0, n=1):
max_new_tokens = 32
input_ids = [128000, 791, 6864, 315, 9822, 374] # The capital of France is
requests.post(self.base_url + "/flush_cache")
response = requests.post(
self.base_url + "/generate",
json={
"input_ids": input_ids,
"sampling_params": {
"temperature": 0 if n == 1 else 0.5,
"max_new_tokens": max_new_tokens,
"n": n,
"stop_token_ids": [119690],
},
"stream": False,
"return_logprob": return_logprob,
"top_logprobs_num": top_logprobs_num,
"logprob_start_len": 0,
},
)
ret = response.json()
print(json.dumps(ret))
output_ids = ret["output_ids"]
requests.post(self.base_url + "/flush_cache")
response_stream = requests.post(
self.base_url + "/generate",
json={
"input_ids": input_ids,
"sampling_params": {
"temperature": 0 if n == 1 else 0.5,
"max_new_tokens": max_new_tokens,
"n": n,
"stop_token_ids": [119690],
},
"stream": True,
"return_logprob": return_logprob,
"top_logprobs_num": top_logprobs_num,
"logprob_start_len": 0,
},
)
ret = response.json()
output_ids = ret["output_ids"]
print("output from non-streaming request:")
print(output_ids)
response_stream_json = []
for line in response_stream.iter_lines():
if line.startswith(b"data: ") and line[6:] != b"[DONE]":
response_stream_json.append(json.loads(line[6:]))
out_stream_ids = []
for x in response_stream_json:
out_stream_ids += x["output_ids"]
print("output from streaming request:")
print(out_stream_ids)
assert output_ids == out_stream_ids
def test_simple_decode(self):
self.run_decode()
def test_parallel_sample(self):
self.run_decode(n=3)
def test_logprob(self):
for top_logprobs_num in [0, 3]:
self.run_decode(return_logprob=True, top_logprobs_num=top_logprobs_num)
def test_eos_behavior(self):
self.run_decode(max_new_tokens=256)
def test_simple_decode_stream(self):
self.run_decode_stream()
if __name__ == "__main__":
unittest.main()