It seems that the official GPU support for OS X has disappeared before I knew it, so if you still want to use GPU, this document may be helpful. Tensorflow 1.6 on macOS High Sierra 10.13.3 with GPU Acceleration (without disabling SIP)
It's easy to install from Tensorflow 1.0.0, so it's recommended to follow the official documentation. https://www.tensorflow.org/install/install_mac
#cuda8.0
$ brew upgrade
$ brew install coreutils
$ brew cask install cuda
#cuDNN v5.1 Download Library for OS X and each/user/local/cuda/How to copy
##.bash_profile
#export CUDA_HOME=/usr/local/cuda
#export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib"
#export DYLD_LIBRARY_PATH="$DYLD_LIBRARY_PATH:$CUDA_HOME/lib"
#export PATH="$CUDA_HOME/bin:$PATH"
#I can do it for the time being, but I will put a link because a warning will appear
$ cd /usr/local/cuda/lib
$ sudo ln -s libcuda.dylib libcuda.1.dylib
$ easy_install --upgrade pip
$ easy_install --upgrade six
$ pip install tensorflow-gpu
In the official Tensorflow repository, Issue # 664 commit: Enable building with CUDA support on Mac OS X / tensorflow / commit / 59faa82c072c473551b25695431fab613675bf24) has been merged.
Now that you can officially use the GPU on your Mac, let's install it immediately.
Reference: [How to compile tensorflow with CUDA support on OSX (Updated 2nd May 2016)](https://medium.com/@fabmilo/how-to-compile-tensorflow-with-cuda-support-on-osx-fd27108e27e1 # .tudz318t1)
$ brew update
$ brew cask info cuda
cuda: 7.5.20
$ bazel version
Build label: 0.2.1-homebrew
Download cuDNN from NVIDIA https://developer.nvidia.com/cudnn
Tensorflow version 0.8 is cuDNN v5, version 0.7 and below is v4
I downloaded cudnn-7.5-osx-x64-v5.0-rc.tgz
.
Unzip the file and move it to the specified position
$tar xzvf ~/Downloads/cudnn-7.5-osx-x64-v5.0-rc.tgz
$sudo mv -v cuda/lib/libcudnn* /usr/local/cuda/lib
$sudo mv -v cuda/include/cudnn.h /usr/local/cuda/include
In .bash_profile
export DYLD_LIBRARY_PATH=/usr/local/cuda/lib:$DYLD_LIBRARY_PATH
Add
$cd Tensorflow repo
$ git pull
$ git checkout master
$ TF_UNOFFICIAL_SETTING=1 ./configure
Please specify the location of python. [Default is /usr/local/bin/python]:
Do you wish to build TensorFlow with GPU support? [y/N] y
GPU support will be enabled for TensorFlow
Please specify which gcc nvcc should use as the host compiler. [Default is /usr/bin/gcc]:
Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: 7.5
Please specify the location where CUDA 7.5 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
Please specify the Cudnn version you want to use. [Leave empty to use system default]: 5
Please specify the location where cuDNN 5 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
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.
Please note that each additional compute capability significantly increases your build time and binary size. [Default is: "3.5,5.2"]: 3.0
Setting up Cuda include
Setting up Cuda lib
Setting up Cuda bin
Setting up Cuda nvvm
Setting up CUPTI include
Setting up CUPTI lib64
Configuration finished
$ bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
...It takes quite a while...
$ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
$ pip install /tmp/tensorflow_pkg/tensorflow-0.8.0-py2-none-any.whl
It may be possible to buy such a thing. BizonBOX 2 (External Graphics Card for Mac)
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