How to install CUDA, cuDNN, TensorFlow and Keras on Ubuntu 16.04

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__)
```

IMP lab