FastDeploy/docs/en/build_and_install/a311d.md

How to Build A311D Deployment Environment

FastDeploy supports AI deployment on Rockchip Soc based on Paddle-Lite backend. For more detailed information, please refer to: PaddleLite Deployment Example.

This document describes how to compile the PaddleLite-based C++ FastDeploy cross-compilation library.

The relevant compilation options are described as follows:

Compile Options	Default Values	Description	Remarks
ENABLE_LITE_BACKEND	OFF	It needs to be set to ON when compiling the A311D library	-
WITH_TIMVX	OFF	It needs to be set to ON when compiling the A311D library	-
TARGET_ABI	NONE	It needs to be set to arm64 when compiling the A311D library	-

For more compilation options, please refer to Description of FastDeploy compilation options

Cross-compilation environment construction

Host Environment Requirements

• os：Ubuntu == 16.04
• cmake： version >= 3.10.0

Building the compilation environment

You can enter the FastDeploy/tools/timvx directory and use the following command to install:

cd FastDeploy/tools/timvx
bash install.sh

You can also install it with the following commands:

 # 1. Install basic software
apt update
apt-get install -y --no-install-recommends \
  gcc g++ git make wget python unzip

# 2. Install arm gcc toolchains
apt-get install -y --no-install-recommends \
  g++-arm-linux-gnueabi gcc-arm-linux-gnueabi \
  g++-arm-linux-gnueabihf gcc-arm-linux-gnueabihf \
  gcc-aarch64-linux-gnu g++-aarch64-linux-gnu

# 3. Install cmake 3.10 or above
wget -c https://mms-res.cdn.bcebos.com/cmake-3.10.3-Linux-x86_64.tar.gz && \
  tar xzf cmake-3.10.3-Linux-x86_64.tar.gz && \
  mv cmake-3.10.3-Linux-x86_64 /opt/cmake-3.10 && \
  ln -s /opt/cmake-3.10/bin/cmake /usr/bin/cmake && \
  ln -s /opt/cmake-3.10/bin/ccmake /usr/bin/ccmake

FastDeploy cross-compilation library compilation based on PaddleLite

After setting up the cross-compilation environment, the compilation command is as follows:

# Download the latest source code
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy  
mkdir build && cd build

# CMake configuration with A311D toolchain
cmake -DCMAKE_TOOLCHAIN_FILE=./../cmake/toolchain.cmake \
      -DWITH_TIMVX=ON  \
      -DTARGET_ABI=arm64 \
      -DCMAKE_INSTALL_PREFIX=fastdeploy-tmivx \
      -DENABLE_VISION=ON \ # 是否编译集成视觉模型的部署模块，可选择开启
      -Wno-dev ..

# Build FastDeploy A311D C++ SDK
make -j8
make install

After the compilation is complete, the fastdeploy-tmivx directory will be generated, indicating that the FastDeploy library based on PadddleLite TIM-VX has been compiled.

Prepare the Soc environment

Before deployment, ensure that the version of the driver galcore.so of the Verisilicon Linux Kernel NPU meets the requirements. Before deployment, please log in to the development board, and enter the following command through the command line to query the NPU driver version. The recommended version of the Rockchip driver is: 6.4.4.3

dmesg | grep Galcore

If the current version does not comply with the above, please read the following content carefully to ensure that the underlying NPU driver environment is correct.

There are two ways to modify the current NPU driver version:

1. Manually replace the NPU driver version. (recommend)
2. flash the machine, and flash the firmware that meets the requirements of the NPU driver version.

Manually replace the NPU driver version

1. Use the following command to download and decompress the PaddleLite demo, which provides ready-made driver files

wget https://paddlelite-demo.bj.bcebos.com/devices/generic/PaddleLite-generic-demo.tar.gz
tar -xf PaddleLite-generic-demo.tar.gz

2. Use uname -a to check Linux Kernel version, it is determined to be version 4.19.111.
3. Upload galcore.ko under PaddleLite-generic-demo/libs/PaddleLite/linux/arm64/lib/verisilicon_timvx/viv_sdk_6_4_4_3/lib/a311d/4.9.113 path to the development board.
4. Log in to the development board, enter sudo rmmod galcore on the command line to uninstall the original driver, and enter sudo insmod galcore.ko to load the uploaded device driver. (Whether sudo is needed depends on the actual situation of the development board. For some adb-linked devices, please adb root in advance). If this step fails, go to method 2.
5. Enter dmesg | grep Galcore in the development board to query the NPU driver version, and it is determined to be: 6.4.4.3

flash

According to the specific development board model, ask the development board seller or the official website customer service for the firmware and flashing method corresponding to the 6.4.4.3 version of the NPU driver.

For more details, please refer to: PaddleLite prepares the device environment

Deployment example based on FastDeploy on A311D

1. For deploying the PaddleClas classification model on A311D, please refer to: C++ deployment example of PaddleClas classification model on A311D

2. For deploying PPYOLOE detection model on A311D, please refer to: C++ deployment example of PPYOLOE detection model on A311D

3. For deploying YOLOv5 detection model on A311D, please refer to: C++ Deployment Example of YOLOv5 Detection Model on A311D

4. For deploying PP-LiteSeg segmentation model on A311D, please refer to: C++ Deployment Example of PP-LiteSeg Segmentation Model on A311D