Files
sglang/test/srt/lora/test_lora_radix_cache.py
2025-08-11 10:14:11 -07:00

84 lines
2.5 KiB
Python

# Copyright 2023-2024 SGLang Team
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
import multiprocessing as mp
import random
import unittest
import torch
from utils import CI_MULTI_LORA_MODELS, DEFAULT_PROMPTS, run_lora_test_one_by_one
from sglang.test.runners import HFRunner, SRTRunner
from sglang.test.test_utils import CustomTestCase
PROMPTS = [
"AI is a field of computer science focused on",
"""
### Instruction:
Tell me about llamas and alpacas
### Response:
Llamas are large, long-necked animals with a woolly coat. They have two toes on each foot instead of three like other camelids.
### Question:
What do you know about llamas?
### Answer:
""",
]
class TestLoRARadixCache(CustomTestCase):
def test_lora_radix_cache(self):
# Here we need a model case with multiple adaptors for testing correctness of radix cache
model_case = CI_MULTI_LORA_MODELS[0]
torch_dtype = torch.float16
max_new_tokens = 32
backend = "triton"
batch_prompts = (
PROMPTS
if not model_case.skip_long_prompt
else [p for p in PROMPTS if len(p) < 1000]
)
# Test lora with radix cache
run_lora_test_one_by_one(
batch_prompts,
model_case,
torch_dtype,
max_new_tokens=max_new_tokens,
backend=backend,
disable_radix_cache=False,
test_tag="lora-with-radix-cache",
)
# Test lora without radix cache
run_lora_test_one_by_one(
batch_prompts,
model_case,
torch_dtype,
max_new_tokens=max_new_tokens,
backend=backend,
disable_radix_cache=True,
test_tag="lora-without-radix-cache",
)
if __name__ == "__main__":
try:
mp.set_start_method("spawn")
except RuntimeError:
pass
unittest.main(warnings="ignore")