This repo is based on the RAI code, including its python bindings. See https://github.com/MarcToussaint/rai for a README of the RAI code.

This assumes a standard Ubuntu 20.04 machine.

• The following assumes $HOME/git as your git path, and $HOME/opt to install 3rd-party libs -- please stick to this (no system-wide installs)

• Install basics

sudo apt-get update
sudo apt-get install git sudo build-essential cmake

• Clone the repo, install Ubuntu packages, & compile with cmake:

mkdir -p $HOME/git
cd $HOME/git
git clone https://github.com/MarcToussaint/optimization-course.git
cd optimization-course

git submodule init
git submodule update

make -j1 printUbuntuAll    # for your information: what the next step will install
make -j1 installUbuntuAll  # calls sudo apt-get install; you can always interrupt

mkdir build
cd build
cmake ..
make -j $(command nproc)

• Install python packages:

pip3 install --user pybind11 jupyter matplotlib

• Test

cd $HOME/git/optimization-course
jupyter-notebook tutorials/how_to_query_an_NLP.ipynb

• When pulling updates for the repo, don't forget to also update the submodules:

git pull
git submodule update

• Install docker engine for Ubuntu as described here, namely:

sudo apt-get update
sudo apt-get install apt-transport-https ca-certificates curl gnupg-agent software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository \
   "deb [arch=amd64] https://download.docker.com/linux/ubuntu \
   $(lsb_release -cs) \
   stable"
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io

• Add your user to the docker user group (otherwise use sudo in front of all docker commands below)

sudo usermod -aG docker ${USER}

Log out and in again!

• Download this docker from docker hub:

docker pull marctoussaint/rai-optim20

• Run the docker, mounting your $HOME directory as ~/home

xhost +local:root
docker run -it \
       --volume="$HOME/:/root/home" \
       --env="DISPLAY" \
       --network host \
       --device /dev/input \
       rai-optim20 /bin/bash

• When running the docker you should get a *** Welcome *** message. You can now run the jupyter server within the docker:

jupyter-notebook optimization-course/tutorials --ip 0.0.0.0 --no-browser --allow-root &

This starts a jupyter server without browser. You can now open your normal Ubuntu browser and access the Jupyter server at http://localhost:8888/?token=... as displayed on the console.

• Whenever you close the docker, the jupyter server and local changes in optimization-course/tutorials get lost. To prevent this, create notbooks in your ~/home directory, which mounts your actual Ubuntu $HOME. (Or mount other paths, as you like.)

• Side note: This is how the docker was created

• From the Microsoft Store, install the 'Ubuntu 20.04 LTS' (which I think is a WSL Ubuntu)

• When you launch it, you get some error on 'component is not enabled'. Follow the https://aka.ms/wslinstall instructions (including reboot)

• Launch the ubuntu

• Install basics

sudo apt-get update
sudo apt-get install git sudo build-essential cmake libjsoncpp-dev --fix-missing

• Follow the 'Compile directly on Ubuntu' instructions

• When launching jupyter, use --no-browser and direct your browser to the link displayed

• Installing X - I wasn't successful

• Install Docker Desktop for Windows

• In a console, pull and run the docker:

docker pull marctoussaint/rai-optim20
docker run -it -p 8888:8888 marctoussaint/rai-optim20 /bin/bash

• Within the docker run jupyter

jupyter-notebook optimization-course/tutorials --ip 0.0.0.0 --allow-root