![]() ![]() MAKE SURE YOU SAY NO TO INSTALLING NVIDIA DRIVERS! Also make sure you select yes to creating a symbolic link to your cuda directory. To install the Nvidia Toolkit download base installation. If you experience any troubles booting linux or logging in: try disabling fast & safe boot in your bios and modifying your grub boot options to enable nomodeset. Once installed using additional drivers restart your computer. $ sudo add-apt-repository ppa:graphics-drivers/ppa You must also have the 367 (or later) NVidia drivers installed, this can easily be done from Ubuntu’s built in additional drivers after you update your driver packages. Paste each line one at a time (without the $) using Shift + Ctrl + V $ sudo apt-get install openjdk-8-jdk git python-dev python3-dev python-numpy python3-numpy python-six python3-six build-essential python-pip python3-pip python-virtualenv swig python-wheel python3-wheel libcurl3-dev libcupti-dev Update & Install Nvidia Drivers Open a terminal by pressing Ctrl + Alt + T ![]() Getting started I am going to assume you know some of the basics of using a terminal in Linux. In order to use TensorFlow with GPU support you must have a Nvidia graphic card with a minimum compute capability of 3.0. If you prefer to build from sources using Ubuntu 14.04 please see my other tutorial. I much prefer to install Tensorflow using Anaconda Python and you can find a tutorial for that here. In this tutorial I will be going through the process of building the latest TensorFlow from sources for Ubuntu 16.04. I have decided to move my blog to my github page, this post will no longer be updated here. ![]()
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