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deeplearning-environment.md

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2. Preparing your deep learning environment

step 1 : os preparation

  • download and install ubuntu 18.04 official link, if you are not sure how to install ubuntu alongside with your current os, follow this link

  • install the necessary libraries

     $ sudo apt-get update
 $ sudo apt-get upgrade -y
 $ sudo apt-get install -y build-essential cmake unzip pkg-config
 $ sudo apt-get install -y libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev
 $ sudo apt-get install -y libjpeg-dev libpng-dev libtiff-dev
 $ sudo apt-get install -y libavcodec-dev libavformat-dev libswscale-dev libv4l-dev
 $ sudo apt-get install -y libxvidcore-dev libx264-dev
 $ sudo apt-get install -y libgtk-3-dev
 $ sudo apt-get install -y libopenblas-dev libatlas-base-dev liblapack-dev gfortran
 $ sudo apt-get install -y libhdf5-serial-dev graphviz
 $ sudo apt-get install -y python3-dev python3-tk python-imaging-tk
 $ sudo apt-get install -y linux-image-generic linux-image-extra-virtual
 $ sudo apt-get install -y linux-source linux-headers-generic

step 2 : nvidia driver & cuda 11.4 (gpu)

  • install nvidia driver

     $ sudo add-apt-repository ppa:graphics-drivers/ppa
 $ sudo apt-get update

 # auto install version
 $ sudo ubuntu-drivers autoinstall 

 # or specify the version ie nvidia-driver-510
 $ sudo apt install nvidia-driver-[version-number]

 - restart your computer
 # verify installation with this command
 $ nvidia-smi

  • if this method doesn't work with you, remove NVIDIA from your system and reinstall .

     # delete nvidia driver
 $ sudo apt-get purge nvidia*

 - restart your pc
 - reinstall nvidia driver

  • download and install cuda 11.4

     $ wget https://developer.download.nvidia.com/compute/cuda/11.4.2/local_installers/cuda_11.4.2_470.57.02_linux.run

 $ sudo sh cuda_11.4.2_470.57.02_linux.run

 # after the installation if cuda isn't in your environment then add it to the files .bashrc

 $ sudo nano ~/.bashrc
 $ export PATH=/usr/local/cuda-11.4/bin${PATH:+:${PATH}}
 $ export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
 $ export CUDA_HOME=/usr/local/cuda

  • download and install cudnn 8.2.4

     $ wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/8.2.2/11.4_07062021/cudnn-11.4-linux-x64-v8.2.2.26.tgz
 $ tar -zvxf cudnn-11.4-linux-x64-v8.2.2.26.tgz
 # add cudnn to your env change xxx with your path
 $ nano ~/.bashrc
 $ export LD_LIBRARY_PATH=xxx/cuda/lib64:$LD_LIBRARY_PATH
 $ source ~/.bashrc
 $ cd xxx/cuda/include
 $ sudo cp *.h /usr/local/cuda/include/
 # replace xxx with your own path
 $ sudo chmod a+r /usr/local/cuda/include/cudnn.h

 # Test that everything is setup
 $ nvidia-smi
 $ nvcc -V

congratulations you are all setup!