Install And Use TensorFlow On CentOS 7

TensorFlow is Google’s open-source platform for machine learning designed to simplify the process of implementing machine-learning models.

Researchers, data scientists, and developers use this end-to-end library for numerical computation. TensorFlow runs on multiple CPUs, GPU, as well as mobile operating systems.

In this tutorial, learn how to install TensorFlow on CentOS 7.

• A CentOS Linux system
• Access to a command line/terminal window (Ctrl+Alt+F2)
• A user account with sudo privileges
• Access to the root user
• Pip 19.0 or later

sudo yum -y install epel-release

yum -y update

If you do not have Python installed on CentOS, run the following command to install pip (a package management system for Python) and the language itself:

sudo yum -y install gcc gcc-c++ python-pip python-devel atlas atlas-devel gcc-gfortran openssl-devel libffi-devel

The output shows that the system downloaded dependencies.

Using the pip command, install and upgrade a virtual environment software. We recommend using Virtualenv, a tool specifically designed for creating isolated Python environments.

Use the following command to install and upgrade Virtualenv on CentOS:

pip install --upgrade virtualenv

Create a new environment by typing:

virtualenv --system-site-packages ~/venvs/tensorflow

Finally, activate the environment:

source ~/venvs/tensorflow/bin/activate

Activating the environment changes the command line prompt, adding the virtual environment’s bin directory as a prefix. This means you are now working inside the virtual environment.

pip install --upgrade tensorflow

pip install --upgrade tensorflow-gpu

Note, TensorFlow with GPU support needs additional hardware and software. To learn more, refer to TensorFlow’s documentation on GPU support.

pip install tensorflow==package_version

For example, to install TensorFlow for CPU version 1.14, type:

pip install tensorflow==1.14

To install TensorFlow for GPU version 1.14, type the command in the following format:

pip install tensorflow-gpu==1.14

TensorFlow 1.15 supports both CPU and GPU workloads in a single package. To install the 1.15 release, run the following command:

pip install tensorflow-gpu==1.15rc2

python -c "import tensorflow as tf;print(tf.reduce_sum(tf.random.normal([1000, 1000])))"