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tensorflow 1.4.0 on windows with avx2 & cuda by cmake
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tensorflow 1.4.0 on windows with avx2 & cuda by cmake | |
win 10 1703 | |
git 2.10.2 | |
cmake 3.8.2 | |
anaconda3 4.4.0 | |
visual studio 2015 update 3 with c++ installed | |
cuda 8.0.61 | |
cudnn 6 | |
swigwin-3.0.10 | |
git clone https://github.com/tensorflow/tensorflow.git -b v1.4.0 | |
cd tensorflow/tensorflow/contrib/cmake | |
mkdir build | |
cd build | |
change compute capabilities (1080ti) | |
tensorflow\tensorflow\contrib\cmake\CMakeLists.txt | |
set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS};-gencode arch=compute_61,code=\"compute_61\") | |
add_definitions(-DGOOGLE_CUDA=1 -DTF_EXTRA_CUDA_CAPABILITIES=6.1) | |
"#define TF_CUDA_CAPABILITIES CudaVersion(\"6.1\")\n" | |
cmake .. -G "Visual Studio 14 2015" -A x64 -T host=x64 ^ | |
-DCMAKE_BUILD_TYPE=Release ^ | |
-DSWIG_EXECUTABLE=C:\Users\User\swigwin-3.0.10\swig.exe ^ | |
-DPYTHON_EXECUTABLE=C:\Users\User\Anaconda3\python.exe ^ | |
-DPYTHON_LIBRARY=C:\Users\User\Anaconda3\libs\python36.lib ^ | |
-Dtensorflow_ENABLE_GPU=ON ^ | |
-DCUDNN_HOME="C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0" ^ | |
-Dtensorflow_WIN_CPU_SIMD_OPTIONS="/arch:AVX2" | |
// MSBuild /p:Configuration=Release tf_python_build_pip_package.vcxproj | |
cmake --build . --target tf_python_build_pip_package --config Release | |
locale win fix | |
tensorflow\tensorflow\contrib\cmake\build\re2\src\re2\CMakeCache.txt:35 | |
CMAKE_CXX_FLAGS:STRING=/DWIN32 /D_WINDOWS /W3 /GR /EHsc /utf-8 | |
2015 avx2 fix | |
https://github.com/tensorflow/tensorflow/pull/13525 | |
pip install tf_python\dist\tensorflow_gpu-1.4.0-cp36-cp36m-win_amd64.whl |
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