Using GPUs for training machine learning applications can speed operations up to 40 times faster than using a common CPU. In this video a stable environment for using TensorFlow 1.3 with CUDA is presented and a simple script is given so we can assure we are using our GPU!

Cuda 8.0 →
cuDNN 6.0 → (requires sign up)
Tensorflow 1.3 →

Pip and virtualenv:

sudo apt-get install python-pip python-dev build-essential
sudo pip install --upgrade pip
sudo pip install --upgrade virtualenv

Create virtual enviroment´s directory:

mkdir my_envs && cd my_envs

Create virtualenv:

virtualenv env

Activate virtualenv:

source env/bin/activate

Installing tensorflow-gpu:

pip install tensorflow-gpu #pip≥8.1

Running the script:


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