compile mxnet cpp api on windows10 using vs2015

In order to deploy MXNet based vision engine to projects develped in C++, we need to compile MXNet CPP API. Though the instruction of how to compile is well illustrated in Build from Source and Build the C++ package, I still confronted some difficulties. This blog records some tips for compling MXNet CPP API.

1. Modify Source Code

   By following the instruction, I could easily complie and get the libmxnet. However, when compling cpp-package, the op.h file can not be generated correctly. In issues#14116, Vigilans provided a solution.

   Here: https://github.com/apache/incubator-mxnet/blob/master/include/mxnet/tuple.h#L744

   namespace dmlc {
   /*! brief description for optional TShape */
   DMLC_DECLARE_TYPE_NAME(optional<mxnet::TShape>, "Shape or None");
   MLC_DECLARE_TYPE_NAME(optional<mxnet::Tuple<int>>, "Shape or None");
   // avoid low version of MSVC
   #if !defined(_MSC_VER) // <----------- Here !
   template<typename T>
   struct type_name_helper<mxnet::Tuple<T> > {
    static inline std::string value() {
        return "tuple of <" + type_name<T>() + ">";
    }
   };
   #endif
   }  // namespace dmlc
   

   So the specialization of mxnet::tuple was disabled for Visual Studio in the first place!
   I removed the #if block, recompile, then everything works fine.

2. Set the Environment Variables

   In my own case, I only needed to set OpenBLAS_HOME and OpenCV_DIR. Both of the can be set by set command or -D in cmake config.

3. Use CMake to generate VS solution

   cmake -G "Visual Studio 14 2015 Win64" -DUSE_CUDA=0 -DUSE_CUDNN=0 -DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_BLAS=open -DUSE_LAPACK=0 -DUSE_DIST_KVSTORE=0 -DUSE_CPP_PACKAGE=1 -DCMAKE_INSTALL_PREFIX=install ..

   Above command can be used to generate a solution without GPU support. By modifying config -DUSE_CUDA and -DUSE_CUDNN, we can generate a solution with GPU support.

4. Generate op.h

   After generating libmxnet, we should run python OpWrapperGenerator.py libmxnet.dll to generate op.h. Note to place libmxnet.dll, libopenblas.dll and libopencv_world.dll together with OpWrapperGenerator.py.

5. No mxnet_static.lib

   The cpp example project failed to link to mxnet_static.lib, which was actually named as libmxnet.lib. I modified the name of the static library. I believe the project settings can be fixed to cope with this problem.