RAGE UDAY KIRAN

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Installing TensorFlow, TensorRT, and Other Machine Learning Libraries

Setting up the Kernal

Installing mainline

sudo add-apt-repository ppa:cappelikan/ppa
sudo apt update
sudo apt install mainline -y
sudo mainline install 6.2

Reboot the Server

sudo reboot

Remove any existing Nvidia installations

sudo apt install gcc
sudo apt-get remove --purge '^nvidia-.*'
sudo apt-get autoremove

Disabling the default NVidia libraries

Open the file

sudo vi /etc/modprobe.d/blacklist-nvidia-nouveau.conf

Insert these lines

blacklist nouveau
options nouveau modeset=0

Save and exit. Regenerate the kernel initramfs.

sudo update-initramfs -u

Check the graphics card by executing the following command:

sudo lshw -C display

Your graphic cards should be shown in the output generated.

Installing Nvidia CUDA libraries

  1. Visit the following URL: https://developer.nvidia.com/cuda-12-2-0-download-archive
  2. Choose your configurations based on your Operating System. Please Choose X86 architecture.
  3. Nvidia will provide you a set of commands to execute. Please execute them one after another by copying and pasting them. An example has been provided below: 
    wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/12.2.0/local_installers/cuda-repo-ubuntu2204-12-2-local_12.2.0-535.54.03-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu2204-12-2-local_12.2.0-535.54.03-1_amd64.deb 
sudo cp /var/cuda-repo-ubuntu2204-12-2-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt update && sudo apt -y install cuda 

sudo reboot
  1. After rebooting the server, execute the following command: 
    nvidia-smi

    You should now see the list of GPUs attached to your machine.

Installing Nvidia cuDNN

  1. Using your Nvidia account, visit the following URL: https://developer.nvidia.com/rdp/cudnn-archive
  2. Download the local installer by choosing the latest version based on your operating system.
  3. Execute the following commands: 
    wget -nc https://www.dropbox.com/scl/fi/ck7akyej5l0onopvmvecf/cudnn-local-repo-ubuntu2204-8.9.7.29_1.0-1_amd64.deb

    sudo dpkg -i cudnn-local-repo-ubuntu2204-8.9.7.29_1.0-1_amd64.deb
sudo cp /var/cudnn-local-repo-ubuntu2204-8.9.7.29/cudnn-local-08A7D361-keyring.gpg /usr/share/keyrings/
sudo apt update && sudo apt install libcudnn8 libcudnn8-dev -y

Installation of NodeJS and NPM

sudo apt-get install -y fuse lvm2 vim plocate curl openssh-server dirmngr gnupg apt-transport-https ca-certificates software-properties-common r-base build-essential libgl1-mesa-glx libegl1-mesa libxrandr2 libxrandr2 libxss1 libxcursor1 libxcomposite1 libasound2 libxi6 libxtst6 gconf-service libasound2 libatk1.0-0 libc6 libcairo2 libcups2 libdbus-1-3 libexpat1 libfontconfig1 libgcc1 libgconf-2-4 libgdk-pixbuf2.0-0 libglib2.0-0 libgtk-3-0 libnspr4 libpango-1.0-0 libpangocairo-1.0-0 libstdc++6 libx11-6 libx11-xcb1 libxcb1 libxcomposite1 libxcursor1 libxdamage1 libxext6 libxfixes3 libxi6 libxrandr2 libxrender1 libxss1 libxtst6 ca-certificates fonts-liberation libappindicator1 libnss3 lsb-release xdg-utils
  
sudo  apt-get  install -y  wget texlive-xetex texlive-full texstudio texmaker texlive-latex-extra pandoc libffi-dev libssl-dev libxml2-dev libxslt1-dev libjpeg8-dev zlib1g-dev python3-pip openssl libssl-dev build-essential gnupg2 vim bash-completion

sudo mkdir -p /etc/apt/keyrings
curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | sudo gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg


NODE_MAJOR=22
echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_$NODE_MAJOR.x nodistro main" | sudo tee /etc/apt/sources.list.d/nodesource.list


sudo apt-get update
sudo apt-get install nodejs -y


node -v   
npm -v

Installing Julia

wget https://julialang-s3.julialang.org/bin/linux/x64/1.8/julia-1.8.0-linux-x86_64.tar.gz
tar -xvzf julia-1.8.0-linux-x86_64.tar.gz
sudo cp -r julia-1.8.0 /opt/
sudo ln -s /opt/julia-1.8.0/bin/julia /usr/local/bin/julia

julia  #to enter into julia interface.
exit   #to edit from julia

Creation and login as a new sudo use`r (Optional)

sudo useradd -m -s /bin/bash -G sudo jupyter

sudo passwd jupyter

su - jupyter

Setting a Virtual Environment using Conda

  1. Download the latest version of Anaconda. 
    wget -nc https://repo.anaconda.com/archive/Anaconda3-2024.10-1-Linux-x86_64.sh
  2. Install the conda 
    bash Anaconda3-2024.10-1-Linux-x86_64.sh

If you face any problem, type the following command:

eval "$(/home/jupyter/anaconda3/bin/conda shell.bash hook)"
  1. Execute the below provided commands 
    source .bashrc
conda config --set auto_activate_base false
  2. Check the Python Version 
    python -V
  3. Tensorflow GPU currently works better if your Python Version is 3.10. Thus, let us create virtual environment with Python 3.10 
    conda create --name jupyterHub python=3.10
  4. Enter into that Virtual Environment 
    conda activate jupyterHub
  5. Execute the following commands 
    pip install --upgrade pip
conda config --add channels conda-forge
conda config --add channels microsoft

conda install -c conda-forge "elyra[all]"

jupyter server extension list

Installing and Setting Up TensorFlow GPU

  1. Install tensorflow-gpu 
    conda install -n base conda-libmamba-solver -y
conda config --set solver libmamba
conda install anaconda::numpy -y
conda install anaconda::scipy -y
conda install conda-forge::cupy -y
conda install anaconda::tensorflow-gpu -y

  2. Check the correctness of installed TensorFlow-gpu by executing the following commands:

    • Approach-1
    python3

    import tensorflow as tf

    Note: If you see any error, such as core dump, then there is a problem.

    • Approach-2
    python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"

    You should be the following output

    [PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU'), PhysicalDevice(name='/physical_device:GPU:1', device_type='GPU')]
  3. Install Keras, PyTorch, and other libraries
pip install tensorflow[and-cuda]

conda install conda-forge::keras -y
conda install -c conda-forge scikit-learn -y
conda install -c rapidsai -c conda-forge -c nvidia dask-cuda cuda-version=12.3 -y
conda install pandas pyarrow -c conda-forge -y
conda install dask distributed -c conda-forge -y
conda install conda-forge::s3fs -y
conda install conda-forge::pytorch-gpu -y
conda install cmake zeromq cppzmq OpenSSL xtl nlohmann_json -c conda-forge -y

python -m pip install torch torch-tensorrt tensorrt pami
#pip install matlab_kernels

Installation of JupterHub

Execute the following commands by staying the jupyterHub environment created in the previous steps.

pip install --upgrade pip
conda install -c conda-forge jupyterlab jupyterhub -y
conda install notebook sidecar playwright -y

conda install -c conda-forge jupyterlab_widgets
conda install conda-forge::configurable-http-proxy -y
#pip install configurable-http-proxy -y

conda install -c conda-forge ipywidgets -y
#pip install ipywidgets

pip install jupyter_contrib_nbextensions
#conda install -c conda-forge jupyter_contrib_nbextensions

conda install -c conda-forge jupyterlab-spellchecker -y
conda install xeus-python notebook -c conda-forge -y
conda install -c conda-forge -c stason ipyexperiments
conda install -c conda-forge rise


conda install conda-forge::jupyterlab-spreadsheet-editor -y
conda install -c conda-forge jupyterlab_vim -y 
conda install -c conda-forge jupyterlab jupyterlab-git -y
conda install jupyter anywidget -y
conda install -c plotly plotly=6.0.0rc0 -y
conda install -c conda-forge python-kaleido -y
conda install -c plotly plotly-geo=1.0.0 -y

conda install bokeh -y
conda install lfortran -c conda-forge -y
conda install jupytext -c conda-forge -y
conda install conda-forge::jupyterlab-latex -y
conda install install xeus-cling -c conda-forge -y
conda install -c conda-forge jupyterlab-drawio -y
conda install -c conda-forge -c plotly jupyter-dash -y


playwright install-deps
playwright install

pip install dockerspawner
pip install aquirdturtle_collapsible_headings
pip install 'itkwidgets[all]>=1.0a49'
conda install -c rapidsai-nightly -c conda-forge jupyterlab-nvdashboard



pip install tqdm jupyterlab-unfold
pip install jupyterlab-code-formatter
pip install black isort
pip install lckr_jupyterlab_variableinspector

pip install tensorflow[and-cuda]

pip install jupyterlab_theme_solarized_dark

pip install pyqt5
conda install qtconsole -y

pip install colabcode
#pip install autots auto-ts darts etna[all] greykite #kats
#error in kats setupfile. 

jupyter contrib nbextension install --user

Setting up the JupyterHub

Come to the home directory.

cd ~

Setup symbolic links to jupyterHub and jupyterNotebook to access them directly from the terminal.

sudo ln -s ~/anaconda3/envs/jupyterHub/bin/jupyter /usr/bin/jupyter
sudo ln -s ~/anaconda3/envs/jupyterHub/bin/jupyterhub /usr/bin/jupyterhub

Create the jupyterHub default configuration file

jupyterhub --generate-config -f ~/jupyterhub_config.py

Open the jupyterHub configuration file

vi ~/jupyterhub_config.py

Add the following text in the file

c.Authenticator.allow_all = True
c.PAMAuthenticator.open_sessions = False
c.JupyterHub.bind_url = 'http://163.143.87.224:80'   #REPLACE the IPADDRESS
c.Spawner.cmd = ['/home/jupyter/anaconda3/envs/jupyterHub/bin/jupyterhub-singleuser']
c.JupyterHub.hub_bind_url = 'http://127.0.0.1:8085'
c.JupyterHub.hub_port = 8082
c.ConfigurableHTTPProxy.command = '/home/jupyter/anaconda3/envs/jupyterHub/bin/configurable-http-proxy'  #'/usr/local/bin/configurable-http-proxy'
c.Spawner.cmd=["/home/jupyter/anaconda3/envs/jupyterHub/bin/jupyter-labhub"]

Note: Change the ipaddress of the variable c.JupyterHub.bind_url

Create a startup file that starts jupyterHub right after the server starts

sudo vi /usr/lib/systemd/system/jupyterhub.service

Copy and Paste the below-provided text:

[Unit]
Description=JupyterHub

[Service]
Type=simple
PIDFile=/run/jupyterhub.pid
# Step 1 and Step 2 details are here..
# ------------------------------------
ExecStart=jupyterhub -f /home/jupyter/jupyterhub_config.py
#User=root
#Group=root
#WorkingDirectory=/home/jupter
Restart=always
RestartSec=10
#KillMode=mixed

[Install]
WantedBy=multi-user.target

Save and exit.

Execute the below commands on the terminal

sudo systemctl enable jupyterhub.service
sudo systemctl daemon-reload
sudo systemctl restart jupyterhub.service

Change the home directory permissions

sudo chmod -R 755 .

Reboot the system

sudo reboot

wget https://github.com/SpencerPark/IJava/releases/download/v1.3.0/ijava-1.3.0.zip

mkdir ijava
mv ijava-1.3.0.zip ./ijava
unzip ijava-1.3.0.zip 
python3 install.py --sys-prefix