Difference between revisions of "NPU/zh"

Latest revision as of 10:00, 8 November 2024

English

1 Earlier version RKNPU2 SDK

Link to → v1.5.2

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-arm64-20241011.img.gz

2.1.2 Ubuntu20 (focal)

rk3588-sd-ubuntu-focal-desktop-6.1-arm64-20241011.img.gz

2.2 install rknpu

cd ~
export GIT_SSL_NO_VERIFY=1
git clone https://github.com/airockchip/rknn-toolkit2.git
cd rknn-toolkit2/rknpu2
sudo cp ./runtime/Linux/librknn_api/aarch64/* /usr/lib
sudo cp ./runtime/Linux/rknn_server/aarch64/usr/bin/* /usr/bin/

2.3 check rknn version

$ strings /usr/bin/rknn_server |grep 'build@'
2.2.0 (3e10681 build@2024-09-06T10:26:49)
rknn_server version: 2.2.0 (3e10681 build@2024-09-06T10:26:49)
$ strings /usr/lib/librknnrt.so |grep 'librknnrt version:'
librknnrt version: 2.2.0 (c195366594@2024-09-14T12:18:56)

2.4 run rknn_yolov5_demo

sudo apt-get update
sudo apt-get install -y gcc g++ make cmake
 
# fix broken link
cd ~/rknn-toolkit2/rknpu2/examples/3rdparty/mpp/Linux/aarch64
rm -f librockchip_mpp.so librockchip_mpp.so.1
ln -s librockchip_mpp.so.0 librockchip_mpp.so
ln -s librockchip_mpp.so.0 librockchip_mpp.so.1
 
cd ~/rknn-toolkit2/rknpu2/examples/rknn_yolov5_demo
chmod +x ./build-linux.sh
sudo ln -s /usr/bin/gcc /usr/bin/aarch64-gcc
sudo ln -s /usr/bin/g++ /usr/bin/aarch64-g++
export GCC_COMPILER=aarch64
./build-linux.sh -t rk3588 -a aarch64 -b Release
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 ~/rknn-toolkit2
pip3 install ./rknn-toolkit-lite2/packages/rknn_toolkit_lite2-2.2.0-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/resnet18/
$ python3 test.py
W rknn-toolkit-lite2 version: 2.2.0
--> Load RKNN model
done
--> Init runtime environment
I RKNN: [06:50:39.456] RKNN Runtime Information, librknnrt version: 2.2.0 (c195366594@2024-09-14T12:18:56)
I RKNN: [06:50:39.456] RKNN Driver Information, version: 0.9.3
I RKNN: [06:50:39.456] RKNN Model Information, version: 6, toolkit version: 2.2.0(compiler version: 2.2.0 (c195366594@2024-09-14T12:24:14)), target: RKNPU v2, target platform: rk3588, framework name: PyTorch, framework layout: NCHW, model inference type: static_shape
W RKNN: [06:50:39.474] query RKNN_QUERY_INPUT_DYNAMIC_RANGE error, rknn model is static shape type, please export rknn with dynamic_shapes
W Query dynamic range failed. Ret code: RKNN_ERR_MODEL_INVALID. (If it is a static shape RKNN model, please ignore the above warning message.)
done
--> Running model
resnet18
-----TOP 5-----
[812] score:0.999680 class:"space shuttle"
[404] score:0.000249 class:"airliner"
[657] score:0.000013 class:"missile"
[466] score:0.000009 class:"bullet train, bullet"
[895] score:0.000008 class:"warplane, military plane"
 
done

2.6 install rknn_toolkit on ubuntu-focal

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

python3.9 -m pip install --upgrade pip
python3.9 -m pip install opencv-python
 
cd ~
[ -d rknn-toolkit2 ] || git clone https://github.com/airockchip/rknn-toolkit2.git \
    --depth 1 -b master
cd rknn-toolkit2
python3.9 -m pip install \
    ./rknn-toolkit-lite2/packages/rknn_toolkit_lite2-2.2.0-cp39-cp39-linux_aarch64.whl \
    -i https://pypi.tuna.tsinghua.edu.cn/simple/

2.6.3 run python demo on ubuntu-focal

cd ~/rknn-toolkit2/rknn-toolkit-lite2/examples/resnet18/
python3.9 test.py

output:

W rknn-toolkit-lite2 version: 2.2.0
--> Load RKNN model
done
--> Init runtime environment
I RKNN: [09:57:36.101] RKNN Runtime Information, librknnrt version: 2.2.0 (c195366594@2024-09-14T12:18:56)
I RKNN: [09:57:36.101] RKNN Driver Information, version: 0.9.3
I RKNN: [09:57:36.101] RKNN Model Information, version: 6, toolkit version: 2.2.0(compiler version: 2.2.0 (c195366594@2024-09-14T12:24:14)), target: RKNPU v2, target platform: rk3588, framework name: PyTorch, framework layout: NCHW, model inference type: static_shape
W RKNN: [09:57:36.117] query RKNN_QUERY_INPUT_DYNAMIC_RANGE error, rknn model is static shape type, please export rknn with dynamic_shapes
W Query dynamic range failed. Ret code: RKNN_ERR_MODEL_INVALID. (If it is a static shape RKNN model, please ignore the above warning message.)
done
--> Running model
resnet18
-----TOP 5-----
[812] score:0.999680 class:"space shuttle"
[404] score:0.000249 class:"airliner"
[657] score:0.000013 class:"missile"
[466] score:0.000009 class:"bullet train, bullet"
[895] score:0.000008 class:"warplane, military plane"
 
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

@@ Line 1: / Line 1: @@
 [[NPU|English]]
+==Earlier version RKNPU2 SDK==
+Link to → [[NPU_SDK1.5.2/zh|v1.5.2]]
 ==How to test NPU==
 ===OS===
 Tested on the following OS:
 ====Debian11 (bullseye)====
-* rk3588-sd-debian-bullseye-desktop-6.1-arm64-20240116.img.gz
+* rk3588-sd-debian-bullseye-desktop-6.1-arm64-20241011.img.gz
-* rk3568-sd-debian-bullseye-desktop-6.1-arm64-20231113.img.gz
 ====Ubuntu20 (focal)====
-* rk3588-sd-ubuntu-focal-desktop-6.1-arm64-20240116.img.gz
+* rk3588-sd-ubuntu-focal-desktop-6.1-arm64-20241011.img.gz
 ===install rknpu===
 <syntaxhighlight lang="text">
+cd ~
 export GIT_SSL_NO_VERIFY=1
-git clone https://github.com/rockchip-linux/rknpu2.git
+git clone https://github.com/airockchip/rknn-toolkit2.git
-cd rknpu2
+cd rknn-toolkit2/rknpu2
-git checkout tags/v1.5.2 -b v1.5.2
+sudo cp ./runtime/Linux/librknn_api/aarch64/* /usr/lib
-sudo cp ./runtime/RK3588/Linux/librknn_api/aarch64/* /usr/lib
+sudo cp ./runtime/Linux/rknn_server/aarch64/usr/bin/* /usr/bin/
-sudo cp ./runtime/RK3588/Linux/rknn_server/aarch64/usr/bin/* /usr/bin/
 </syntaxhighlight>
 ===check rknn version===
 <syntaxhighlight lang="text">
-strings /usr/bin/rknn_server |grep 'build@'
+$ strings /usr/bin/rknn_server |grep 'build@'
-strings /usr/lib/librknnrt.so |grep 'librknnrt version:'
+.2.0 (3e10681 build@2024-09-06T10:26:49)
+rknn_server version: 2.2.0 (3e10681 build@2024-09-06T10:26:49)
+$ strings /usr/lib/librknnrt.so |grep 'librknnrt version:'
+librknnrt version: 2.2.0 (c195366594@2024-09-14T12:18:56)
 </syntaxhighlight>
@@ Line 29: / Line 33: @@
 sudo apt-get update
 sudo apt-get install -y gcc g++ make cmake
-cd examples/rknn_yolov5_demo
-./build-linux_RK3588.sh
+# fix broken link
+cd ~/rknn-toolkit2/rknpu2/examples/3rdparty/mpp/Linux/aarch64
+rm -f librockchip_mpp.so librockchip_mpp.so.1
+ln -s librockchip_mpp.so.0 librockchip_mpp.so
+ln -s librockchip_mpp.so.0 librockchip_mpp.so.1
+cd ~/rknn-toolkit2/rknpu2/examples/rknn_yolov5_demo
+chmod +x ./build-linux.sh
+sudo ln -s /usr/bin/gcc /usr/bin/aarch64-gcc
+sudo ln -s /usr/bin/g++ /usr/bin/aarch64-g++
+export GCC_COMPILER=aarch64
+./build-linux.sh -t rk3588 -a aarch64 -b Release
 cd install/rknn_yolov5_demo_Linux
 ./rknn_yolov5_demo model/RK3588/yolov5s-640-640.rknn model/bus.jpg
@@ Line 46: / Line 60: @@
 sudo apt-get update
 sudo apt-get install -y python3-dev python3-numpy python3-opencv python3-pip
-cd ~
+cd ~/rknn-toolkit2
-git clone https://github.com/rockchip-linux/rknn-toolkit2.git
+pip3 install ./rknn-toolkit-lite2/packages/rknn_toolkit_lite2-2.2.0-cp39-cp39-linux_aarch64.whl -i https://pypi.tuna.tsinghua.edu.cn/simple/
-(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/
 </syntaxhighlight>
 ====run python demo====
 <syntaxhighlight lang="text">
-$ cd rknn-toolkit2/rknn_toolkit_lite2/examples/inference_with_lite/
+$ cd ~/rknn-toolkit2/rknn-toolkit-lite2/examples/resnet18/
 $ python3 test.py
+W rknn-toolkit-lite2 version: 2.2.0
 --> 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: [06:50:39.456] RKNN Runtime Information, librknnrt version: 2.2.0 (c195366594@2024-09-14T12:18:56)
-I RKNN: [08:06:49.416] RKNN Driver Information: version: 0.9.2
+I RKNN: [06:50:39.456] RKNN Driver Information, version: 0.9.3
-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-
+I RKNN: [06:50:39.456] RKNN Model Information, version: 6, toolkit version: 2.2.0(compiler version: 2.2.0 (c195366594@2024-09-14T12:24:14)), target: RKNPU v2, target platform: rk3588, framework name: PyTorch, framework layout: NCHW, model inference type: static_shape
-T09:35:42)), target: RKNPU v2, target platform: rk3588, framework name: PyTorch, framework layout: NCHW, model inference type: static_s
+W RKNN: [06:50:39.474] query RKNN_QUERY_INPUT_DYNAMIC_RANGE error, rknn model is static shape type, please export rknn with dynamic_shapes
-hape
+W Query dynamic range failed. Ret code: RKNN_ERR_MODEL_INVALID. (If it is a static shape RKNN model, please ignore the above warning message.)
 done
 --> Running model
 resnet18
 -----TOP 5-----
-[812]: 0.9996760487556458
+[812] score:0.999680 class:"space shuttle"
-[404]: 0.00024927023332566023
+[404] score:0.000249 class:"airliner"
-[657]: 1.449744013370946e-05
+[657] score:0.000013 class:"missile"
-[466 833]: 9.023910024552606e-06
+[466] score:0.000009 class:"bullet train, bullet"
-[466 833]: 9.023910024552606e-06
+[895] score:0.000008 class:"warplane, military plane"
 done
 </syntaxhighlight>
-===install rknn_toolkit on ubuntu===
+===install rknn_toolkit on ubuntu-focal===
 ====build python3.9 from source====
 <syntaxhighlight lang="text">
@@ Line 94: / Line 107: @@
 ====install rknn_toolkit====
 <syntaxhighlight lang="text">
-pip install --upgrade pip
+python3.9 -m pip install --upgrade pip
-pip install opencv-python
+python3.9 -m pip install opencv-python
 cd ~
-git clone https://github.com/rockchip-linux/rknn-toolkit2.git
+[ -d rknn-toolkit2 ] || git clone https://github.com/airockchip/rknn-toolkit2.git \
-(cd rknn-toolkit2 && git checkout tags/v1.5.2 -b v1.5.2)
+    --depth 1 -b master
-/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/
+cd rknn-toolkit2
+python3.9 -m pip install \
+    ./rknn-toolkit-lite2/packages/rknn_toolkit_lite2-2.2.0-cp39-cp39-linux_aarch64.whl \
+    -i https://pypi.tuna.tsinghua.edu.cn/simple/
 </syntaxhighlight>
-====run python demo====
+====run python demo on ubuntu-focal====
 <syntaxhighlight lang="text">
-$ cd rknn-toolkit2/rknn_toolkit_lite2/examples/inference_with_lite/
+cd ~/rknn-toolkit2/rknn-toolkit-lite2/examples/resnet18/
-$ python3 test.py
+python3.9 test.py
+</syntaxhighlight>
+output:
+<syntaxhighlight lang="text">
+W rknn-toolkit-lite2 version: 2.2.0
 --> 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: [09:57:36.101] RKNN Runtime Information, librknnrt version: 2.2.0 (c195366594@2024-09-14T12:18:56)
-I RKNN: [08:41:08.078] RKNN Driver Information: version: 0.9.2
+I RKNN: [09:57:36.101] RKNN Driver Information, version: 0.9.3
-I RKNN: [08:41:08.080] RKNN Model Information: version: 6, toolkit version: 1.5.2-source_code(compiler version: 1.5.2 (71720f3fc@
+I RKNN: [09:57:36.101] RKNN Model Information, version: 6, toolkit version: 2.2.0(compiler version: 2.2.0 (c195366594@2024-09-14T12:24:14)), target: RKNPU v2, target platform: rk3588, framework name: PyTorch, framework layout: NCHW, model inference type: static_shape
--08-21T09:35:42)), target: RKNPU v2, target platform: rk3588, framework name: PyTorch, framework layout: NCHW, model inferenc
+W RKNN: [09:57:36.117] query RKNN_QUERY_INPUT_DYNAMIC_RANGE error, rknn model is static shape type, please export rknn with dynamic_shapes
-e type: static_shape
+W Query dynamic range failed. Ret code: RKNN_ERR_MODEL_INVALID. (If it is a static shape RKNN model, please ignore the above warning message.)
 done
 --> Running model
 resnet18
 -----TOP 5-----
-[812]: 0.9996760487556458
+[812] score:0.999680 class:"space shuttle"
-[404]: 0.00024927023332566023
+[404] score:0.000249 class:"airliner"
-[657]: 1.449744013370946e-05
+[657] score:0.000013 class:"missile"
-[466 833]: 9.023910024552606e-06
+[466] score:0.000009 class:"bullet train, bullet"
-[466 833]: 9.023910024552606e-06
+[895] score:0.000008 class:"warplane, military plane"
 done
@@ Line 128: / Line 149: @@
 ==Doc==
 https://github.com/rockchip-linux/rknpu2/tree/master/doc
+==Other==
+===查看NPU占有率===
+<syntaxhighlight lang="text">
+cat /sys/kernel/debug/rknpu/load
+</syntaxhighlight>
+===设置NPU频率===
+<syntaxhighlight lang="text">
+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
+</syntaxhighlight>
+===查看NPU频率===
+<syntaxhighlight lang="text">
+cat /sys/class/devfreq/fdab0000.npu/cur_freq
+</syntaxhighlight>

Difference between revisions of "NPU/zh"

Latest revision as of 10:00, 8 November 2024

Contents

1 Earlier version RKNPU2 SDK

2 How to test NPU

2.1 OS

2.1.1 Debian11 (bullseye)

2.1.2 Ubuntu20 (focal)

2.2 install rknpu

2.3 check rknn version

2.4 run rknn_yolov5_demo

2.5 install rknn_toolkit on debian11

2.5.1 install rknn_toolkit

2.5.2 run python demo

2.6 install rknn_toolkit on ubuntu-focal

2.6.1 build python3.9 from source

2.6.2 install rknn_toolkit

2.6.3 run python demo on ubuntu-focal

3 Doc

4 Other

4.1 查看NPU占有率

4.2 设置NPU频率

4.3 查看NPU频率

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