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Tensorflow 1.4 Mac OS High Sierra 10.13 GPU Support
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Tensorflow_Build_GPU.md

Tensorflow

This allows my Convolutional Neural Network to be trained tad little faster on 2013 MacBookPro15 (4core i7/16GB + NVidia GT750M/2GB) than a 2016 MacPro (6Core Xeon/32GB).

System information

  • OS - High Sierra 10.13
  • Tensorflow - 1.4
  • Xcode command line tools - 8.2 (Download from Xcode - Support - Apple Developer) sudo xcode-select --switch /Library/Developer/CommandLineTools & clang -v
  • Cmake - 3.7
  • Bazel - 0.9.0 via Homebrew
  • CUDA - 9
  • cuDNN - 7

Requirements

  • sudo pip install six numpy wheel
  • brew install coreutils

Step-by-step guide

Remove all align(sizeof(T)) from following files:

  • tensorflow/core/kernels/depthwise_conv_op_gpu.cu.cc

  • tensorflow/core/kernels/split_lib_gpu.cu.cc

  • tensorflow/core/kernels/concat_lib_gpu_impl.cu.cc

    For example, extern shared __align(sizeof(T))__ unsigned char smem[]; => extern shared unsigned char smem[];

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]: y
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]: y
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 
    Note the use of `--incompatible_load_argument_is_label=false` which is needed with Bazel 0.9 and Tensorflow r1.4
bazel build --config=cuda --config=opt --action_env PATH --action_env LD_LIBRARY_PATH --action_env DYLD_LIBRARY_PATH --incompatible_load_argument_is_label=false //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)
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