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Extrodox/Tensorflow GPU 1.4 Mac OS High Sierra 10.13 Support.md

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Last active December 17, 2017 05:11
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Tensorflow GPU 1.4 Mac OS High Sierra 10.13 Support
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Tensorflow GPU 1.4 Mac OS High Sierra 10.13 Support.md

Tensorflow

This is fully functional version of Tensorflow with GPU on macOS 10.13 it also works on 10.13.1 I hope it helps.

System information

  • OS - High Sierra 10.13
  • Tensorflow - 1.4
  • Xcode command line tools - 8.2 (Download from here: Xcode - Support - Apple Developer & Switch to different clang version: sudo xcode-select --switch/Library/Developer/CommandLineTools & check version: clang -v)
  • Cmake - 3.7
  • Bazel - 0.7.0
  • CUDA - 9
  • cuDNN - 7

Clone tensorflow.

git clone --recurse-submodules https://github.com/tensorflow/tensorflow

Requirements

  • sudo pip install six numpy wheel
  • sudo pip install --upgrade setuptools
  • 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]: 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]3.0

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/$USER/lib:/usr/local/cuda/lib:/usr/local/cuda/extras/CUPTI/lib
    • export LD_LIBRARY_PATH=$DYLD_LIBRARY_PATH
    • export PATH=$DYLD_LIBRARY_PATH:$PATH

  • nano tensorflow/third_party/gpus/crosstool/CROSSTOOL_nvcc.tpl

    • search for "cxx_flag"
    • found 2 of them
    • added cxx_flag: "-D_MWAITXINTRIN_H_INCLUDED" after both cxx_flag: "-std=c++11" entries
    • cat -n third_party/gpus/crosstool/CROSSTOOL_nvcc.tpl |grep D_MWAITXINTRIN_H_INCLUDED
      • 53 cxx_flag: "-D_MWAITXINTRIN_H_INCLUDED"
      • 173 cxx_flag: "-D_MWAITXINTRIN_H_INCLUDED"

  • flag -lgomp is not needed as it is in built in LLVM now.

  • remove line linkopts = ["-lgomp"], from following files

    • third_party/gpus/cuda/BUILD.tpl
    • third_party/toolchains/gpus/cuda/BUILD

  • from file tensorflow/contrib/cmake/tf_stream_executor.cmake

    • replace set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -lgomp")
    • with set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")

The line numbers correspond to where I added the current entries.

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

Now go Out side of this directory and test this

> python
import tensorflow as tf
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))

The output will show the device name on which the tensorflow is running. Mine is as follows.

2017-11-24 02:27:09.336265: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:864] OS X does not support NUMA - returning NUMA node zero
2017-11-24 02:27:09.336842: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1062] Found device 0 with properties:
name: GeForce GT 750M major: 3 minor: 0 memoryClockRate(GHz): 0.9255
pciBusID: 0000:01:00.0
totalMemory: 2.00GiB freeMemory: 1.61GiB
2017-11-24 02:27:09.336871: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1152] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GT 750M, pci bus id: 0000:01:00.0, compute capability: 3.0)
Device mapping:
/job:localhost/replica:0/task:0/device:GPU:0 -> device: 0, name: GeForce GT 750M, pci bus id: 0000:01:00.0, compute capability: 3.0
2017-11-24 02:27:10.103507: I tensorflow/core/common_runtime/direct_session.cc:297] Device mapping:
/job:localhost/replica:0/task:0/device:GPU:0 -> device: 0, name: GeForce GT 750M, pci bus id: 0000:01:00.0, compute capability: 3.

Congratulations! You are awesome :)

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