C+ code for deployment on Android, Windows, linux, MacOS

Environment setup

Build requirements:

• Git (for clone codes and submodules)

git clone --recurse-submodules git@git.woa.com:InteractionAlgorithm/Juglans.git

• CMake 3.21.0 or later
• C++ 17 compiler
  • MSVC 2017 version 15.7 or later, MSVC 2022 is recommended.
  • GCC 7.0 or later
  • Clang 6.0 or later
  • Android NDK r17, see instructions below
• (Optional) If build with command line, install make, jom or ninja. Recommend to use ninja on Windows and make on other platforms.
• Have clang-format 14 in PATH, see Code format section for details.
• TensorRT (Windows and Linux), see instructions below

Android Setup

These steps assumes you haven't installed Android SDK or NDK before. If you already has Android SDK, you can install NDK r17c and set it folder as ANDROID_NDK_r17c environment variable.

It's recommended to use NDK r17c to match the same version that is used by SNPE.

1. Download Tencent JDK 8.
2. Extract binary and set TencentKona-8.xxx folder as JAVA_HOME environment variable
3. Add TencentKona-8.xxx/bin folder to PATH
4. Download Android command line tools.
5. Extract binary to a temp place
6. Create a new folder for android sdk on the disk. Referred as <Android SDK Path> in following commands.
7. Run cmdline-tools\bin\sdkmanager.bat --sdk_root=<Android SDK Path> "cmdline-tools;latest" platform-tools "ndk;21.4.7075529"
8. Add <Android SDK Path>\platform-tools and optionally <Android SDK Path>\cmdline-tools\latest\bin to PATH.
9. Set <Android SDK Path>\ndk\21.4.7075529 as ANDROID_NDK_r21e environment variable.
10. Remove the temp command line tools

Install TensorRT

1. Install latest NVIDIA GPU driver from official website
2. Install CUDA Toolkit 11.3 Update 1, which is same version used by Pytorch in Hawthorn.

• On Windows, download and run setup exe. Make sure unselect GPU driver as we have installed newer version in previous step.
• On Linux (including WSL2), follow instruction on pages to install with package manager.

3. Register NVIDIA developer account, which is required to download cuDNN and TensorRT.
4. Download and install latest cuDNN for CUDA 11.x

• On Windows, extract zip file and add bin subfolder to PATH.
• On Windows, extract zlibwapi.dll from zlib release and put in cuDNN bin folder (or any other foler in PATH).

5. Download and install lastest TensorRT GA for CUDA 11.x.

• On Windows, extract zip file and add lib & bin subfolders to PATH.

Build Instructions

Build on Windows using VS

Run the following commands in command line to generate VS solution and projects, assuming current workdir is root of juglans repo.

md build
cd build
cmake -G "Visual Studio 17 2022" ..
start Juglans.sln

If you are using older VS version, change cmake generator to Visual Studio 15 2017 Win64 or Visual Studio 16 2019.

Build on Windows using Commane Line

1. Open Developer Command Prompt for VS
2. Run following commands to generate ninja makefiles, assuming current workdir is root of juglans repo.

md build
cd build
cmake -G Ninja -DCMAKE_BUILD_TYPE=Release ..

3. To build targets, run ninja <target>.

Build for Android

1. Make sure ANDROID_NDK_r17c environment variable is set.
2. Run following commands to generate ninja makefiles, assuming current workdir is root of juglans repo.

md build
cd build
cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -DANDROID=ON ..

3. To build targets, run ninja <target>.

Available targets

1. Module targets: juglans_<module>, e.g. juglans_core.
2. Tool targets: <tool>, e.g. capture.
3. Test targets: <module>_test, e.g. core_test.
4. Run test targets (command line generator only): run_<module>_test or run_all to run all tests.
5. Unity related targets: unity to copy binaries to unity demo's plugin folder.
6. Code format targets: clangformat to format all, or clangformat_<module>/clangformat_<tool> to format only 1 module/tool.

Code format

We use clang-foramt 14 to format all source files in the repo.

Install

• Windows
  1. Download LLVM-14.0.5-win64.exe from release page
  2. Install LLVM and add bin folder to PATH.
  3. Alternatively, copy clang-format.exe from bin folder and put it in any folder inside PATH.
• Mac

brew install clang-format@14

• Ubuntu
  • Ubuntu 18.04

  echo "deb http://apt.llvm.org/bionic/ llvm-toolchain-bionic-14 main" | sudo tee /etc/apt/sources.list.d/llvm.list
  echo "deb-src http://apt.llvm.org/bionic/ llvm-toolchain-bionic-14 main" | sudo tee -a /etc/apt/sources.list.d/llvm.list
  wget -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
  sudo add-apt-repository -y ppa:ubuntu-toolchain-r/test
  sudo apt install clang-format-14
  

  • Ubuntu 20.04 or newer

  echo "deb http://apt.llvm.org/$(lsb_release -cs)/ llvm-toolchain-$(lsb_release -cs)-14 main" | sudo tee /etc/apt/sources.list.d/llvm.list
  echo "deb-src http://apt.llvm.org/$(lsb_release -cs)/ llvm-toolchain-$(lsb_release -cs)-14 main" | sudo tee -a /etc/apt/sources.list.d/llvm.list
  wget -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
  sudo apt update
  sudo apt install clang-format-14
  

Format

Build clangformat target generated by CMake. This can be clangformat project in your VS solution or make clangforamt depending on your CMake generator.