Build PaddlePaddle for iOS

This tutorial will walk you through cross compiling the PaddlePaddle library for iOS from the source in MacOS.


Apple provides Xcode for cross-compiling and IDE for iOS development. Download from App store or here. To verify your installation, run command as follows

$ xcodebuild -version
Xcode 9.0
Build version 9A235

Cross-compiling configurations

PaddlePaddle provides cross-compiling toolchain configuration documentation cmake/cross_compiling/ios.cmake, which has some default settings for frequently used compilers.

There are some mandatory environment variables need to be set before cross compiling PaddlePaddle for iOS:

  • CMAKE_SYSTEM_NAME, CMake compiling target platform name, has to be iOS. PaddlePaddle CMake will compile all the third party dependencies and enforce some parameters (WITH_C_API=ON, WITH_GPU=OFF, WITH_AVX=OFF, WITH_PYTHON=OFF,WITH_RDMA=OFF) when this variable is set with value iOS.
  • WITH_C_API, Whether to compile inference C-API library, has to be ON, since C-API is the only supported interface for inferencing in iOS.
  • WITH_SWIG_PY, has to be OFF. It’s not supported to inference or train via swig in iOS.

Optional environment variables for iOS are:

  • IOS_PLATFORM, either OS (default) or SIMULATOR.

    • OS, build targets ARM-based physical devices like iPhone or iPad.
    • SIMULATOR, build targets x86 architecture simulators.
  • IOS_ARCH, target architecture. By default, all architecture types will be compiled. If you need to specify the architecture to compile for, please find valid values for different IOS_PLATFORM settings from the table below:

    OS armv7, armv7s, arm64
    SIMULATOR i386, x86_64
  • IOS_DEPLOYMENT_TARGET, minimum iOS version to deployment, 7.0 by default.

  • IOS_ENABLE_BITCODE, whether to enable Bitcode, values can be ON/OFF, ON by default.

  • IOS_USE_VECLIB_FOR_BLAS, whether to use vecLib framework for BLAS computing. values can be ON/OFF, OFF by default.

  • IOS_DEVELOPMENT_ROOT, the path to Developer directory, can be explicitly set with your /path/to/platform/Developer. If left blank, PaddlePaddle will automatically pick the Xcode corresponding platform‘s Developer directory based on your IOS_PLATFORM value.

  • IOS_SDK_ROOT, the path to SDK root, can be explicitly set with your /path/to/platform/Developer/SDKs/SDK. if left black, PaddlePaddle will pick the latest SDK in the directory of IOS_DEVELOPMENT_ROOT.

other settings:

  • USE_EIGEN_FOR_BLAS, whether to use Eigen for matrix computing. effective when IOS_USE_VECLIB_FOR_BLAS=OFF. Values can be ON/OFF, OFF by default.
  • HOST_C/CXX_COMPILER, host C/C++ compiler. Uses value from environment variable CC/CXX by default or cc/c++ if CC/CXX doesn’t exist.

some typical cmake configurations:

      -DIOS_ARCH="armv7;arm64" \
      -DCMAKE_INSTALL_PREFIX=your/path/to/install \
      -DWITH_C_API=ON \
      -DIOS_ARCH="x86_64" \
      -DCMAKE_INSTALL_PREFIX=your/path/to/install \
      -DWITH_C_API=ON \

You can set other compiling parameters for your own need. I.E. if you are trying to minimize the library size, set CMAKE_BUILD_TYPE with MinSizeRel; or if the performance is your concern, set CMAKE_BUILD_TYPE with Release. You can even manipulate the PaddlePaddle compiling procedure by manually set CMAKE_C/CXX_FLAGS values.

TIPS for a better performance:

  • set CMAKE_BUILD_TYPE with Release

Build and install

After CMake, run following commands, PaddlePaddle will download the compile 3rd party dependencies, compile and install PaddlePaddle inference library.

$ make
$ make install

Please Note: if you compiled PaddlePaddle in the source directory for other platforms, do remove third_party and build directory within the source with rm -rf to ensure that all the 3rd party libraries dependencies and PaddlePaddle is newly compiled with current CMake configuration.

your/path/to/install directory will have following directories after make install:

  • include, contains all the C-API header files.
  • lib, contains PaddlePaddle C-API static library.
  • third_party contains all the 3rd party libraries.

Please note: if PaddlePaddle library need to support both physical devices and simulators, you will need to compile correspondingly, then merge fat library with lipo.

Now you will have PaddlePaddle library compiled and installed, the fat library can be used in deep learning related iOS APPs. Please refer to C-API documentation for usage guides.