tensorflow-gpu 2.0 Ubuntu 18.04 Setup

cuda-setup.sh

#!/bin/sh
# Install latest Nvidia Drivers
sudo apt-get install nvidia-driver-440

# Download latest version of CUDA supported by TF GPU: https://www.tensorflow.org/install/source#gpu
# NOTE: Do NOT install the driver provided by the CUDA installer when it asks you if you want it
wget https://developer.nvidia.com/compute/cuda/10.0/Prod/local_installers/cuda_10.0.130_410.48_linux
sudo sh cuda_10.0.130_410.48_linux.sh

# Install Latest cuDNN Libraries supported by TF GPU: https://www.tensorflow.org/install/source#gpu
# NOTE: cuDNN 7.6.4 for CUDA 10.0 also seems to work depending on which version of cuDNN was compiled with your
# GPU drivers. Leaving 7.4.2 in the gist since the cuDNN version seems to vary depending on which version
# was compiled with the GPU drivers
wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v7.4.2/prod/10.0_20181213/cudnn-10.0-linux-x64-v7.4.2.24.tgz
tar -zxvdf cudnn-10.0-linux-x64-v7.4.2.24.tgz
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-10.0/lib64/
sudo cp  cuda/include/cudnn.h /usr/local/cuda-10.0/include/
sudo chmod a+r /usr/local/cuda-10.0/include/cudnn.h /usr/local/cuda/lib64/libcudnn*

# Update system libraries
sudo bash -c "echo /usr/local/cuda/lib64/ > /etc/ld.so.conf.d/cuda.conf"
sudo ldconfig

# Install Anaconda and pre-reqs
sudo apt-get install libgl1-mesa-glx libegl1-mesa libxrandr2 libxrandr2 libxss1 libxcursor1 libxcomposite1 libasound2 libxi6 libxtst6
wget https://repo.anaconda.com/archive/Anaconda3-2019.10-Linux-x86_64.sh
sh Anaconda3-2019.10-Linux-x86_64.sh
source .zshrc

# Setup Anaconda environment
conda create -n py37tfgpu python=3.7 anaconda
conda activate py37tfgpu
pip install tensorflow-gpu
pip install keras

# Cleanup
rm cuda_10.0.130_410.48_linux.sh cudnn-10.0-linux-x64-v7.4.2.24.tgz Anaconda3-2019.10-Linux-x86_64.sh
rm -rf cuda/