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https://github.com/zylo117/tensorflow-gpu-macosx

Unoffcial NVIDIA CUDA GPU support version of Google Tensorflow for MAC OSX
https://github.com/zylo117/tensorflow-gpu-macosx

dist gpu mac osx python tensor tensorflow-gpu-macosx

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Unoffcial NVIDIA CUDA GPU support version of Google Tensorflow for MAC OSX

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# tensorflow-gpu-macosx



Unoffcial NVIDIA CUDA GPU support version of Google Tensorflow 1.8 for MAC OSX 10.13



**Description:**



    Since Google Tensorflow claimed that tensorflow-gpu no longer supports 

    MAC OSX since 1.2.0 due to the OpenMP issue of clang of Apple,

    I built this unoffcial tensorflow-gpu for MAC OSX so that

    Hackintosh users or Mac users with eGPU can run tensorflow-gpu with CUDA.



**Requirement:**



    1. Must use python3 instead of python2



    2. Must be installed on MAC OSX 10.6+



    3. Must install Nvidia GPU drivers



    4. Must install Nvidia CUDA toolkit 9.1 (if not, you need to re-compile by yourself)



    5. Must install Nvidia CUDA cudnn 7.0 (if not, you need to re-compile by yourself)



    6. Must set up cuda environment (make sure 'nvcc -V' shows the cuda version '9.1')



    7.CUDA compute capability is in [3.0,5.0] (if not, you need to re-compile to get a better performance)



# HOW TO BUILD TENSORFLOW-GPU FOR MAC OSX?



## NOTICE 



1.INSTALL NVIDIA DRIVER



2.INSTALL NVIDIA CUDA TOOLKIT (9.1 OR LATER)



3.INSTALL NVIDIA CUDA CUDNN (7.0 OR LATER)



4.SET UP CUDA ENVIRONMENT (MAKE SURE



    nvcc -V



WORKS AND PRINTS CUDA VERSION)



5.INSTALL XCODE/COMMAND LINE TOOL 9.3+



6.INSTALL HOMEBREW



7.INSTALL COREUTILS USING 



    brew install coreutils



**8.INSTALL LLVM USING**



    brew install llvm

    

**9.INSTALL OPENMP USING** 



    brew install cliutils/apple/libomp



**10.INSTALL BAZEL 0.16.1 FROM GITHUB**

*(https://github.com/bazelbuild/bazel/releases, newer/older version may cause failure)*



12.GIT CLONE TENSORFLOW



    git clone https://github.com/zylo117/tensorflow-gpu-macosx



13.CD TENSORFLOW SOURCE DIR



14.CONFIG(skip this step if your CUDA version is same as mine)



    ./configure

      #Please specify the location of python.: Accept the default option

        #Please input the desired Python library path to use.:  Accept the default option

        #Do you wish to build TensorFlow with Google Cloud Platform support? [Y/n]: n

        #Do you wish to build TensorFlow with Hadoop File System support? [Y/n]: n

        #Do you wish to build TensorFlow with Amazon S3 File System support? [Y/n]: n

        #Do you wish to build TensorFlow with XLA JIT support? [y/N]: n

        #Do you wish to build TensorFlow with GDR support? [y/N]: n

        #Do you wish to build TensorFlow with VERBS support? [y/N]: n

        #Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]: n

        #Do you wish to build TensorFlow with CUDA support? [y/N]: y

        #Please specify the CUDA SDK version you want to use, e.g. 7.0.: 9.1

        #Please specify the location where CUDA 9.1 toolkit is installed.: Accept the default option

        #Please specify the cuDNN version you want to use.: 7

        #Please specify the location where cuDNN 7 library is installed.: Accept the default option

        ##Please specify a list of comma-separated Cuda compute capabilities you want to build with.

        ##You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus. (GTX10X0: 6.1, GTX9X0: 5.2)

        #Please note that each additional compute capability significantly increases your build time and binary size.: 6.1,5.2,5.0,3.0

        #Do you want to use clang as CUDA compiler? [y/N]: n

        #Please specify which gcc should be used by nvcc as the host compiler.: Accept the default option

        #Do you wish to build TensorFlow with MPI support? [y/N]: n

        #Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified:  Accept the default option

        #Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]: n



    export CUDA_HOME=/usr/local/cuda

    export DYLD_LIBRARY_PATH=/usr/local/cuda/lib:/usr/local/cuda/extras/CUPTI/lib

    export LD_LIBRARY_PATH=$DYLD_LIBRARY_PATH

    export PATH=$DYLD_LIBRARY_PATH:$PATH



    # bazel clean --expunge # Use this if you failed to compile before.



**15.BUILD**



    bazel build --config=cuda --config=opt --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" --action_env PATH --action_env LD_LIBRARY_PATH --action_env DYLD_LIBRARY_PATH //tensorflow/tools/pip_package:build_pip_package



**16.NCCL PATCH**

  

  You can compile NCCL_OPS by yourself (not necessary):



    gcc -c -fPIC ./nccl_patched/nccl_ops.cc -o ./nccl_patched/_nccl_ops.o

    

    gcc ./nccl_patched/_nccl_ops.o -shared -o ./nccl_patched/_nccl_ops.so

  

  Then replace the original nccl lib:



    mv ./bazel-bin/tensorflow/contrib/nccl/python/ops/_nccl_ops.so ./bazel-bin/tensorflow/contrib/nccl/python/ops/_nccl_ops.so.bk



    cp ./nccl_patched/_nccl_ops.so ./bazel-bin/tensorflow/contrib/nccl/python/ops/



16.BUILD PYTHON BINDING USING



    ./bazel-bin/tensorflow/tools/pip_package/build_pip_package/ ./tmp/tensorflow_pkg



17.INSTALL PYTHON WHEEL USING 'pip3 install /tmp/tensorflow_pkg/*.whl'



18.REINSTALL XCODE/COMMAND LINE TOOL 9



**NOTICE**



    This version will not supports multi-cpu/machine training.

    

    It's not like you are gonna need it anyway.



**INSTALL:**



    **Either compile from src through pypi (not recommended)**

        pip3 install tensorflow-gpu-macosx

    **or install from relese (the easiest way)**

        pip3 install *.whl