This installation guide is tested on Ubuntu 16.04 LTS (please don’t use no LTS version).
- Download CUDA toolkit. Actually the latest version is the 9.1, but is not well configured for the use with TensorFlow and Keras. Then please install CUDA 9.0 (see the legacy releases box).
sudo dpkg -i cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64.deb sudo apt-key add /var/cuda-repo-/7fa2af80.pub sudo apt update sudo apt install cuda
After the installation, please also install the patches, if they are available.
- Download cuDNN (tar file). This step requires a registration to nVidia website. After the registration, select the version of cudNN, that matches with the version of CUDA, that you have installed on your PC. Now the correct version of cuDNN is the v.7.1.2 for CUDA 9.0.
Installation steps:tar -xzvf cudnn-9.0-linux-x64-v7.tgz
sudo cp cuda/include/cudnn.h /usr/local/cuda/include sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
- Open a terminal and install python or python3 and pip
sudo apt install python3 python3-pip
- Install TensorFlow (https://www.tensorflow.org/install/install_linux) GPU-version. Check to staify all the prerequisites
sudo apt-get install cuda-command-line-tools
and then install the package using pip
sudo pip3 install tensorflow-gpu
- Install Keras (https://keras.io/) through pip
sudo pip3 install keras
That’s all!
Test correct installation
- Open a terminal
- Open a python shell
python3
- Import TensorFlow
import tensorflow as tf
- Check if the import will produce some mistakes. If there are not errors you have terminated and you can view the version of the installed TensorFlow
print(tf.__version__)