How to set up tensorflow with CUDA 8 cuDNN 5.1 in virtualenv with Python 3.5 on Ubuntu 16.04 http://ksopyla.com/2017/02/tensorflow-gpu-virtualenv-python3/

ubuntu16_tensorflow_cuda8.sh

# This is shorthened version of blog post 
#  http://ksopyla.com/2017/02/tensorflow-gpu-virtualenv-python3/

# update packages
sudo apt-get update
sudo apt-get upgrade

#Add the ppa repo for NVIDIA graphics driver
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update

#Install the recommended driver (currently nvidia-378)
sudo ubuntu-drivers autoinstall
sudo reboot

#check if drivers were installed
nvidia-smi





#############################################
# Instal CUDA Toolkit 8.0 for x64 Ubuntu 16.04 
#wget -O cuda_8_linux.run https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda_8.0.61_375.26_linux-run
#sudo chmod +x cuda_8_linux.run
#./cuda_8.0.61_375.26_linux.run

# BETTER WAY: Download the cuda 8 repo deb package from cuda website. install cuda-8-0 meta package. 


#Do you accept the previously read EULA?
#accept
#Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 367.48?
#n (we installed drivers previously)
#Install the CUDA 8.0 Toolkit?
#y
#Enter Toolkit Location:
#/usr/local/cuda-8.0 (enter)
#Do you wish to run the installation with ‚sudo’?
#y
#Do you want to install a symbolic link at /usr/local/cuda?
#y 
#Install the CUDA 8.0 Samples?
#y 
#Enter CUDA Samples Location:
#enter 

# Install cuDNN
# go to website and download cudnn-8 https://developer.nvidia.com/cudnn
tar -zxvf cudnn-8.0-linux-x64-v5.1.tgz 

# copy libs to /usr/local/cuda folder
sudo cp -P cuda/include/cudnn.h /usr/local/cuda/include
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*

# isntall python 3 and virtual env
sudo apt install python3-pip
sudo apt install python3-venv

# create virtual environment for tensorflow
python3 -m venv tfenv
source tfenv/bin/activate

# Instal tensorflow package with gpu support
(tfenv)$ pip install tensorflow-gpu
#or CPU version
(tfenv)$ pip install tensorflow


# check installation, run simple python scipt from console
$ python

import tensorflow as tf
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcuda.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcurand.so locally
tf_session = tf.Session()
x = tf.constant(1)
y = tf.constant(1)
print(tf_session.run(x + y))