Tensorflow

Note From Tensorflow Official Site: As of version 1.2, TensorFlow no longer provides GPU support on macOS.

This repo try to build tensorflow-gpu on macOS

Thanks for https://gist.github.com/smitshilu/53cf9ff0fd6cdb64cca69a7e2827ed0f

Download

You can find whl files in release dir.

py2 py3

System information

• OS - High Sierra 10.13
• Tensorflow - 1.5
• Xcode command line tools - 8.3.2
• Cmake - 3.10.1
• Bazel - 0.9.0-homebrew
• CUDA - 9.1
• cuDNN - 7

Requirements

• sudo pip install six numpy wheel
• brew install coreutils

Steps:

• Disable SIP (in recovery mode enter command: csrutil disable)
• ./configure (Find CUDA compute value from https://developer.nvidia.com/cuda-gpus)

  Smit-Shilu:tensorflow-build smitshilu$ ./configure
  You have bazel 0.7.0-homebrew installed.
  Please specify the location of python. [Default is /Users/smitshilu/anaconda3/bin/python]:
  
  Found possible Python library paths:
    /Users/smitshilu/anaconda3/lib/python3.6/site-packages
  Please input the desired Python library path to use.  Default is [/Users/smitshilu/anaconda3/lib/python3.6/site-packages]
  
  Do you wish to build TensorFlow with Google Cloud Platform support? [Y/n]: n
  No Google Cloud Platform support will be enabled for TensorFlow.
  
  Do you wish to build TensorFlow with Hadoop File System support? [Y/n]: n
  No Hadoop File System support will be enabled for TensorFlow.
  
  Do you wish to build TensorFlow with Amazon S3 File System support? [Y/n]: n
  No Amazon S3 File System support will be enabled for TensorFlow.
  
  Do you wish to build TensorFlow with XLA JIT support? [y/N]: n
  No XLA JIT support will be enabled for TensorFlow.
  
  Do you wish to build TensorFlow with GDR support? [y/N]: n
  No GDR support will be enabled for TensorFlow.
  
  Do you wish to build TensorFlow with VERBS support? [y/N]: n
  No VERBS support will be enabled for TensorFlow.
  
  Do you wish to build TensorFlow with OpenCL support? [y/N]: n
  No OpenCL support will be enabled for TensorFlow.
  
  Do you wish to build TensorFlow with CUDA support? [y/N]: y
  CUDA support will be enabled for TensorFlow.
  
  Please specify the CUDA SDK version you want to use, e.g. 7.0. [Leave empty to default to CUDA 8.0]: 9.0
  
  Please specify the location where CUDA 9.0 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 default to cuDNN 6.0]: 7
  
  Please specify the location where cuDNN 7 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]6.1
  
  Do you want to use clang as CUDA compiler? [y/N]:
  nvcc will be used as CUDA compiler.
  
  Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:
  
  Do you wish to build TensorFlow with MPI support? [y/N]:
  No MPI support will be enabled for TensorFlow.
  
  Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]:
  
  Add "--config=mkl" to your bazel command to build with MKL support.
  Please note that MKL on MacOS or windows is still not supported.
  If you would like to use a local MKL instead of downloading, please set the environment variable "TF_MKL_ROOT" every time before build.
  Configuration finished
  

• Add following paths:
  • export CUDA_HOME=/usr/local/cuda
  • export DYLD_LIBRARY_PATH=/Users/USERNAME/lib:/usr/local/cuda/lib:/usr/local/cuda/extras/CUPTI/lib (Replace USERNAME with your machine username)
  • export LD_LIBRARY_PATH=$DYLD_LIBRARY_PATH
  • export PATH=$DYLD_LIBRARY_PATH:$PATH
• Start build

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

• Generate a wheel for installation

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

• Install tensorflow wheel

  sudo pip install /tmp/tensorflow_pkg/tensorflow-1.4.0rc1-cp36-cp36m-macosx_10_7_x86_64.whl (File name depends on tensorflow version and python version)