1ffca8673f
### What this PR does / why we need it?
Add basic 310p support. Only dense models work with eager mode now.
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
---------
Signed-off-by: Tflowers-0129 <2906339855@qq.com>
Signed-off-by: Shaoxu Cheng <2906339855@qq.com>
79 lines
2.7 KiB
Python
79 lines
2.7 KiB
Python
#
|
|
# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
|
|
# Copyright 2023 The vLLM 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.
|
|
# This file is a part of the vllm-ascend project.
|
|
import pytest
|
|
from vllm.assets.image import ImageAsset
|
|
|
|
from tests.e2e.conftest import VllmRunner
|
|
|
|
|
|
@pytest.mark.parametrize("dtype", ["float16"])
|
|
@pytest.mark.parametrize("max_tokens", [5])
|
|
def test_llm_models(dtype: str, max_tokens: int) -> None:
|
|
example_prompts = [
|
|
"Hello, my name is",
|
|
"The future of AI is",
|
|
]
|
|
|
|
with VllmRunner("Qwen/Qwen3-0.6B",
|
|
tensor_parallel_size=1,
|
|
dtype=dtype,
|
|
max_model_len=2048,
|
|
enforce_eager=True) as vllm_model:
|
|
vllm_model.generate_greedy(example_prompts, max_tokens)
|
|
|
|
|
|
@pytest.mark.skip(reason="310P: multimodal test skipped, offline is ok")
|
|
@pytest.mark.parametrize("dtype", ["float16"])
|
|
def test_multimodal_vl(dtype: str):
|
|
image = ImageAsset("cherry_blossom").pil_image.convert("RGB")
|
|
|
|
img_questions = [
|
|
"What is the content of this image?",
|
|
"Describe the content of this image in detail.",
|
|
"What's in the image?",
|
|
"Where is this image taken?",
|
|
]
|
|
|
|
images = [image] * len(img_questions)
|
|
placeholder = "<|image_pad|>"
|
|
prompts = [
|
|
("<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n"
|
|
f"<|im_start|>user\n<|vision_start|>{placeholder}<|vision_end|>"
|
|
f"{q}<|im_end|>\n<|im_start|>assistant\n") for q in img_questions
|
|
]
|
|
|
|
with VllmRunner("Qwen/Qwen2.5-VL-3B-Instruct",
|
|
mm_processor_kwargs={
|
|
"min_pixels": 28 * 28,
|
|
"max_pixels": 1280 * 28 * 28,
|
|
"fps": 1,
|
|
},
|
|
dtype=dtype,
|
|
max_model_len=8192,
|
|
enforce_eager=True,
|
|
limit_mm_per_prompt={"image": 1}) as vllm_model:
|
|
outputs = vllm_model.generate_greedy(
|
|
prompts=prompts,
|
|
images=images,
|
|
max_tokens=64,
|
|
)
|
|
|
|
assert len(outputs) == len(prompts)
|
|
|
|
for _, output_str in outputs:
|
|
assert output_str, "Generated output should not be empty."
|