tensorflow-gpu and nvidia rtx 2060 / 2070 / 2080

cuda_installation_on_ubuntu_18.04

#!/bin/bash
## This gist contains step by step instructions to install cuda v9.0 and cudnn 7.2 in ubuntu 18.04

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

### killing literally anything nvidia
sudo /usr/local/cuda-X.Y/bin/uninstall_cuda_X.Y.pl # X.Y version number
sudo /usr/bin/nvidia-uninstall
sudo rm /etc/apt/sources.list.d/cuda*
sudo apt-get remove --purge '^nvidia-.*'
sudo apt remove nvidia-*


### to verify your gpu is cuda enable check
lspci | grep -i nvidia

### gcc compiler is required for development using the cuda toolkit. to verify the version of gcc install enter
gcc --version

# first get the PPA repository driver
sudo add-apt-repository ppa:graphics-drivers/ppa

# install nvidia driver 
sudo apt install nvidia-driver-410

# install other import packages
sudo apt-get install g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev

# CUDA 9 requires gcc 6
sudo apt install gcc-6
sudo apt install g++-6

# downoad one of the "runfile (local)" installation packages from cuda toolkit archive 
wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/cuda_9.0.176_384.81_linux-run

# make the download file executable
chmod +x cuda_9.0.176_384.81_linux.run 
sudo ./cuda_9.0.176_384.81_linux.run --override

# answer following questions while installation begin
# You are attempting to install on an unsupported configuration. Do you wish to continue? y
# Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 384.81? n
# Install the CUDA 9.0 Toolkit? y

# set up symlinks for gcc/g++
sudo ln -s /usr/bin/gcc-6 /usr/local/cuda/bin/gcc
sudo ln -s /usr/bin/g++-6 /usr/local/cuda/bin/g++

# setup your paths
echo 'export PATH=/usr/local/cuda-9.0/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
source ~/.bashrc

# install cuDNN v7.2
# in order to download cuDNN you have to be regeistered here https://developer.nvidia.com/developer-program/signup
# then download cuDNN v7.2 form https://developer.nvidia.com/cudnn
CUDNN_TAR_FILE="cudnn-9.0-linux-x64-v7.2.1.38"
wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v7.2.1/prod/9.0_20180806/${CUDNN_TAR_FILE}
tar -xzvf ${CUDNN_TAR_FILE}

# copy the following files into the cuda toolkit directory.
sudo cp -P cuda/include/cudnn.h /usr/local/cuda-9.0/include
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-9.0/lib64/
sudo chmod a+r /usr/local/cuda-9.0/lib64/libcudnn*

# Finally, to verify the installation, check
nvidia-smi
nvcc -V

# You will want to reboot now...
sudo reboot

# Now simply get tensorflow
pip install tensorflow-gpu==1.12.0

# Test whether tf finds your gpu
python -c "import tensorflow as tf;tf.test.gpu_device_name()"
# you should see something like this