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Build Tensorflow with GPU

Enabling GPU & CPU support with Tensorflow 2.2

• CentOS 7.x
• Python 3.7
• CUDA 10.1
• GCC 7.3.1

Installing Bazel

Download the corresponding .repo file from Fedora COPR and copy it to /etc/yum.repos.d/.
Run the following command:

# yum install bazel3

Installing GCC 7

The SCL repositories provide a package named Developer Toolset, which includes newer versions of the GNU Compiler Collection, and other development and debugging tools.

# yum install centos-release-scl

install the Developer Toolset version 7.

# yum install devtoolset-7

To access GCC version 7, you need to launch a new shell instance using the Software Collection scl tool:

# scl enable devtoolset-7 bash

Download the TensorFlow source code

Use Git to clone the TensorFlow repository:

# git clone https://github.com/tensorflow/tensorflow.git 
# cd tensorflow
              

Configure

# ./configure

Compile

# bazel build --config=opt --config=cuda --config=noaws --config=nogcp --config=nohdfs --config=numa //tensorflow/tools/pip_package:build_pip_package

Build The Package

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

Install the package

The filename of the generated .whl file depends on the TensorFlow version and your platform. Use pip install to install the package, for example:

$ pip install /tmp/tensorflow_pkg/tensorflow-2.2.0-cp37-cp37m-linux_x86_64.whl

Testing

show GPU device: