Conversation
# 华为NPU适配方法
## 测试环境
### NPU相关软件版本
1. NPU驱动
npu-smi 25.0.rc1.1 Version: 25.0.rc1.1
2. CANN相关
- ./Ascend-cann-toolkit_8.5.0_linux-aarch64.run --install
- ./Ascend-cann-{npu-version}-ops_8.5.0_linux-aarch64.run --install # 请根据不同型号下载不同安装程序
### 依赖包安装
1. pip install torch==2.8.0 pytorch-wpe pytorch-wavelets rotary-embedding-torch torch-complex torchaudio
2. pip install torch_npu==2.8.0
3. pip install funasr==1.3.1
## 代码修改
### 模型适配代码
修改 ~/funasr/auto/auto_model.py
```
try:
import torch_npu
npu_is_available = torch_npu.npu.is_available()
except ImportError:
npu_is_available = False
build_model(**kwargs):
...
or (device == "npu" and not npu_is_available)
...
```
### 测试验证代码
```
from funasr import AutoModel
model = AutoModel(
model="iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
disable_update=True,
device="npu"
)
res = model.generate(
input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav"
hotword="达摩院 磨搭",
)
print(res)
```
Summary of ChangesHello @xtuhcy, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request integrates support for Huawei NPU devices into the Highlights
🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console. Changelog
Activity
Using Gemini Code AssistThe full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips. Invoking Gemini You can request assistance from Gemini at any point by creating a comment using either
Customization To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a Limitations & Feedback Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here. You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension. Footnotes
|
![gemini-code-assist[bot]](https://avatars.githubusercontent.com/in/956858?s=60&v=4){kind=small}
| try: | ||
| import torch_npu | ||
| npu_is_available = torch_npu.npu.is_available() | ||
| except ImportError: | ||
| npu_is_available = False |
There was a problem hiding this comment.
为了与 torch.cuda.is_available() 等检查保持一致性，并提高代码的封装性，建议将NPU可用性检查封装在一个函数中。这样可以避免在模块加载时就尝试导入 torch_npu，只在需要时执行检查。请在 build_model 方法中也相应地调用此函数。
| try: | |
| import torch_npu | |
| npu_is_available = torch_npu.npu.is_available() | |
| except ImportError: | |
| npu_is_available = False | |
| def is_npu_available(): | |
| """检查NPU是否可用。""" | |
| try: | |
| import torch_npu | |
| return torch_npu.npu.is_available() | |
| except ImportError: | |
| return False |
| if ((device =="cuda" and not torch.cuda.is_available()) | ||
| or (device == "xpu" and not torch.xpu.is_available()) | ||
| or (device == "mps" and not torch.backends.mps.is_available()) | ||
| or (device == "npu" and not npu_is_available) |
There was a problem hiding this comment.
为了与建议的 is_npu_available() 函数保持一致，请在此处调用该函数进行检查。
| or (device == "npu" and not npu_is_available) | |
| or (device == "npu" and not is_npu_available()) |
1 participant
华为NPU适配方法
测试环境
NPU相关软件版本
npu-smi 25.0.rc1.1 Version: 25.0.rc1.1
依赖包安装
代码修改
模型适配代码
修改 ~/funasr/auto/auto_model.py
测试验证代码