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Tensorflow

Motivation

I have CUDA 9.1 installed for macOS High Sierra (10.13.1), and installed tensorflow-gpu through pip. However, when I tried to run the object detection sample python object_detection/builders/model_builder_test.py, I got an ImportError

Library not loaded: @rpath/libcublas.8.0.dylib

It was looking for CUDA 8.0 while I have CUDA 9.1. Instead of installing CUDA 8.0, I decided to try compiling tensorflow from scratch with GPU support for CUDA 9.1.

System information

  • OS - High Sierra 10.13.1
  • Tensorflow - 1.6.0rc1 (git master as of 2018/02/20)
  • Xcode command line tools - 8.3.3 (9.0 does not work)
  • Cmake - 3.10.2 (Homebrew)
  • Bazel - 0.10.1 (Homebrew)
  • CUDA - 9.1 (NVIDIA)
  • cuDNN - 7.0 (NVIDIA)

Requirements

  • I use python3 in virtualenv, which is activated before the following pip install
  • pip install six numpy wheel
  • brew install coreutils gcc

Step-by-step guide

Switch to Xcode 8.3.3

  • cd ~/Downloads
  • unzip Xcode8.3.3.xip
  • sudo mv Xcode.app /Applications/Xcode-8.3.3.app
  • sudo xcode-select -s /Applications/Xcode-8.3.3.app
  • /usr/bin/gcc --version
Configured with: --prefix=/Applications/Xcode-8.3.3.app/Contents/Developer/usr --with-gxx-include-dir=/usr/include/c++/4.2.1
Apple LLVM version 8.1.0 (clang-802.0.42)
Target: x86_64-apple-darwin17.2.0
Thread model: posix
InstalledDir: /Applications/Xcode-8.3.3.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin

Link gomp library of gcc by Homebrew

  • sudo ln -s /usr/local/Cellar/gcc/7.3.0/lib/gcc/7/libgomp.dylib /usr/local/lib/libgomp.dylib

Remove ALL occurrences align(sizeof(T)) from following files:

  • tensorflow/core/kernels/depthwise_conv_op_gpu.cu.cc (4 places)

  • 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__ /*__align__(sizeof(T))*/ unsigned char smem[];

Steps:

You have bazel 0.10.1-homebrew installed.
Please specify the location of python. [Default is ...]: /usr/local/Cellar/python3/3.6.4_2/bin/python3


Found possible Python library paths:
  /usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages
Please input the desired Python library path to use.  Default is [...] /usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages
Do you wish to build TensorFlow with Google Cloud Platform support? [Y/n]: 
Google Cloud Platform support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Hadoop File System support? [Y/n]: 
Hadoop File System support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Amazon S3 File System support? [Y/n]: 
Amazon S3 File System support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Apache Kafka Platform support? [y/N]: y
Apache Kafka Platform support will be enabled for TensorFlow.

Do you wish to build TensorFlow with XLA JIT support? [y/N]: 
No XLA JIT support will be enabled for TensorFlow.

Do you wish to build TensorFlow with GDR support? [y/N]: 
No GDR support will be enabled for TensorFlow.

Do you wish to build TensorFlow with VERBS support? [y/N]: 
No VERBS support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]: 
No OpenCL SYCL 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 9.0]: 9.1


Please specify the location where CUDA 9.1 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 7.0]: 


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]


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]: 


Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]: 
Not configuring the WORKSPACE for Android builds.

Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See tools/bazel.rc for more details.
    --config=mkl         	# Build with MKL support.
    --config=monolithic  	# Config for mostly static monolithic 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 (make sure to uninstall tensorflow and tensorflow-gpu before installing below) 
    pip install --upgrade dask
pip install /tmp/tensorflow_pkg/tensorflow-1.6.0rc1-cp36-cp36m-macosx_10_12_x86_64.whl (File name depends on tensorflow version and python version)