NPU SDK1.5.2/zh

English

1 New version RKNPU2 SDK

Link to → NPU

2 How to test NPU

2.1 OS

Tested on the following OS:

2.1.1 Debian11 (bullseye)

• rk3588-sd-debian-bullseye-desktop-6.1-arm64-20240116.img.gz
• rk3568-sd-debian-bullseye-desktop-6.1-arm64-20231113.img.gz

2.1.2 Ubuntu20 (focal)

• rk3588-sd-ubuntu-focal-desktop-6.1-arm64-20240116.img.gz

2.2 install rknpu

export GIT_SSL_NO_VERIFY=1
git clone https://github.com/rockchip-linux/rknpu2.git
cd rknpu2
git checkout tags/v1.5.2 -b v1.5.2
sudo cp ./runtime/RK3588/Linux/librknn_api/aarch64/* /usr/lib
sudo cp ./runtime/RK3588/Linux/rknn_server/aarch64/usr/bin/* /usr/bin/

2.3 check rknn version

strings /usr/bin/rknn_server |grep 'build@'
strings /usr/lib/librknnrt.so |grep 'librknnrt version:'

2.4 run rknn_yolov5_demo

sudo apt-get update
sudo apt-get install -y gcc g++ make cmake
cd examples/rknn_yolov5_demo
./build-linux_RK3588.sh
 
cd install/rknn_yolov5_demo_Linux
./rknn_yolov5_demo model/RK3588/yolov5s-640-640.rknn model/bus.jpg

Transfer the generated out.jpg to PC to view the result:

scp out.jpg xxx@YourIP:/tmp/

2.5 install rknn_toolkit on debian11

2.5.1 install rknn_toolkit

sudo apt-get update
sudo apt-get install -y python3-dev python3-numpy python3-opencv python3-pip
cd ~
git clone https://github.com/rockchip-linux/rknn-toolkit2.git
(cd rknn-toolkit2 && git checkout tags/v1.5.2 -b v1.5.2)
pip3 install ./rknn-toolkit2/rknn_toolkit_lite2/packages/rknn_toolkit_lite2-1.5.2-cp39-cp39-linux_aarch64.whl -i https://pypi.tuna.tsinghua.edu.cn/simple/

2.5.2 run python demo

$ cd rknn-toolkit2/rknn_toolkit_lite2/examples/inference_with_lite/
$ python3 test.py
--> Load RKNN model
done
--> Init runtime environment
I RKNN: [08:06:49.416] RKNN Runtime Information: librknnrt version: 1.5.2 (c6b7b351a@2023-08-23T15:28:22)
I RKNN: [08:06:49.416] RKNN Driver Information: version: 0.9.2
I RKNN: [08:06:49.416] RKNN Model Information: version: 6, toolkit version: 1.5.2-source_code(compiler version: 1.5.2 (71720f3fc@2023-08-
21T09:35:42)), target: RKNPU v2, target platform: rk3588, framework name: PyTorch, framework layout: NCHW, model inference type: static_s
hape
done
--> Running model
resnet18
-----TOP 5-----
[812]: 0.9996760487556458
[404]: 0.00024927023332566023
[657]: 1.449744013370946e-05
[466 833]: 9.023910024552606e-06
[466 833]: 9.023910024552606e-06
 
done

2.6 install rknn_toolkit on ubuntu

2.6.1 build python3.9 from source

sudo apt install build-essential libssl-dev libffi-dev software-properties-common \
    libbz2-dev libncurses-dev libncursesw5-dev libgdbm-dev liblzma-dev libsqlite3-dev \
    tk-dev libgdbm-compat-dev libreadline-dev
 
wget https://www.python.org/ftp/python/3.9.16/Python-3.9.16.tar.xz
tar -xvf Python-3.9.16.tar.xz
cd Python-3.9.16/
./configure --enable-optimizations
make -j$(nproc)
sudo make install

2.6.2 install rknn_toolkit

pip install --upgrade pip
pip install opencv-python
cd ~
git clone https://github.com/rockchip-linux/rknn-toolkit2.git
(cd rknn-toolkit2 && git checkout tags/v1.5.2 -b v1.5.2)
/usr/local/bin/python3.9 -m pip install ./rknn-toolkit2/rknn_toolkit_lite2/packages/rknn_toolkit_lite2-1.5.2-cp39-cp39-linux_aarch64.whl -i https://pypi.tuna.tsinghua.edu.cn/simple/

2.6.3 run python demo

$ cd rknn-toolkit2/rknn_toolkit_lite2/examples/inference_with_lite/
$ python3 test.py
--> Load RKNN model
done
--> Init runtime environment
I RKNN: [08:41:08.078] RKNN Runtime Information: librknnrt version: 1.5.2 (c6b7b351a@2023-08-23T15:28:22)
I RKNN: [08:41:08.078] RKNN Driver Information: version: 0.9.2
I RKNN: [08:41:08.080] RKNN Model Information: version: 6, toolkit version: 1.5.2-source_code(compiler version: 1.5.2 (71720f3fc@
2023-08-21T09:35:42)), target: RKNPU v2, target platform: rk3588, framework name: PyTorch, framework layout: NCHW, model inferenc
e type: static_shape
done
--> Running model
resnet18
-----TOP 5-----
[812]: 0.9996760487556458
[404]: 0.00024927023332566023
[657]: 1.449744013370946e-05
[466 833]: 9.023910024552606e-06
[466 833]: 9.023910024552606e-06
 
done

3 Doc

https://github.com/rockchip-linux/rknpu2/tree/master/doc

4 Other

4.1 查看NPU占有率

cat /sys/kernel/debug/rknpu/load

4.2 设置NPU频率

echo userspace > /sys/class/devfreq/fdab0000.npu/governor
echo 800000000 > /sys/class/devfreq/fdab0000.npu/min_freq
echo 1000000000 > /sys/class/devfreq/fdab0000.npu/max_freq

4.3 查看NPU频率

cat /sys/class/devfreq/fdab0000.npu/cur_freq