在centos6环境下安装TensorFlow

The official-released binary packages of TensorFlow are built for newer version of Linux distros. Here is how to build TensorFlow binary package for CentOS 6.

Install Dependencies

Admin privilege is required here.

OpenJDK (for Bazel)

Install OpenJDK

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yum install java-1.8.0-openjdk-devel

Developer Toolset (for Bazel and TensorFlow)

C++11 compatible compiler is required during the building process. Follow the instructions in this article to install Developer Toolset. It is worth noting that, in this case, installing just devtoolset-6-toolchain would be sufficient.

Python 2.7 (for TensorFlow)

This step also requires Software Collections installed. Therefore, if you’ve installed Developer Toolset by following the instructions above, you should have no problem installing these dependencies.

Install Python 2.7

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yuminstallpython27python27-numpypython27-python-develpython27-python-wheel

Build and Install Bazel

Enter Build Environment

Enter Software Collection environment with Developer Toolset.

Setup Build Environment

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scl enable devtoolset-6 bash

Prepare Source Code

Method 1 (Recommended)

The standard way of compiling a release version of Bazel from source is to use a distribution archive. From version 0.4.1, bootstrapping Bazel from GitHub repository is no longer supported as only the distribution archives contain generated artifacts required for direct compilation. Download bazel-<VERSION>-dist.zip from the release page.

Preparation

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# download distribution archive

wgethttps://github.com/bazelbuild/bazel/releases/download/0.4.5/bazel-0.4.5-dist.zip

unzipbazel-0.4.5-dist.zip-dbazel-0.4.5-dist

cdbazel-0.4.5-dist

Method 2 (Only Works for Version <= 0.4.0)

Preparation

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# clone source code repository

git clone https://github.com/bazelbuild/bazel.git

cd bazel

 

# select version (optional)

git checkout 0.4.0

Build and Install

Build and Install

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# compile

./compile.sh

 

# install

mkdir-p~/bin

cpoutput/bazel~/bin/

 

# exit from Software Collection environment

exit

Build TensorFlow with Bazel

Enter Build Environment

Enter Software Collection environment with Developer Toolset and Python 2.7.

Setup Build Environment

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scl enable devtoolset-6 python27 bash

Prepare Source Code

Preparation

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# clone source code repository

gitclonehttps://github.com/tensorflow/tensorflow.git

cdtensorflow

 

# select version (optional)

gitcheckoutv1.1.0

Since GNU C library version in CentOS 6 is less than 2.17, a slight modification needs to be applied before compilation.

Modify tf_extension_linkopts function in tensorflow/tensorflow.bzl from

Original tf_extension_linkopts Function

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def tf_extension_linkopts():

  return []  # No extension link opts

to

Modified tf_extension_linkopts Function

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deftf_extension_linkopts():

  return["-lrt"]

Build

After above modification, we can now start building!

Remember to disable jemalloc when configuring — otherwise the build will fail.

Build

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# configure workspace, disable jemalloc and leave everything else as default

./configure

 

# build

~/bin/bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package

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

 

# exit from Software Collection environment

exit

Finishing Up

Finally, you will found a tensorflow-1.1.0-cp27-none-linux_x86_64.whl (filename may vary upon versions) in /tmp/tensorflow_pkg/. With this self-built binary package, we can now deploy TensorFlow to CentOS 6 by pip.

Enter Python Environment on Deployment Target

Enter Python 2.7 environment either by Software Collection or by tools like pyenv.

Enter Python 2.7 Environment

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# by Software Collection

sclenablepython27bash

 

# or by pyenv

pyenvshellanaconda2-4.3.1

Install

Depending on your environment setup, admin privilege might be needed here.

Pip Installation

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pipinstalltensorflow-1.1.0-cp27-none-linux_x86_64.whl

References

1. Installing TensorFlow from Sources – TensorFlow
2. Compiling from source – Installing Bazel – Bazel
3. Distribution Artifact for Bazel – Bazel
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