cram2 / cram_teaching

Lectures on CRAM in Jupyter Notebooks via Docker

cram-teaching - quick setup for Ubuntu 20.04

With this guide you will install the docker-compose plugin to run JupyterNotebook with CRAM.

Virtualization

Enable CPU virtualization in your BIOS to run virtual machines (VMs). If VMs are already enabled, there's nothing to do here.

Check if VMs are enabled with kvm-ok

sudo apt-get install cpu-checker

kvm-ok

Set up the Docker repository for aptitude

Reference Manual

1. Update the apt package index and install packages to allow apt to use a repository over HTTPS:

sudo apt-get update

sudo apt-get install ca-certificates curl gnupg

2. Add Docker’s official GPG key:

sudo install -m 0755 -d /etc/apt/keyrings

curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg

sudo chmod a+r /etc/apt/keyrings/docker.gpg

3. Use the following command to set up the repository:

echo \
  "deb [arch="$(dpkg --print-architecture)" signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \
  "$(. /etc/os-release && echo "$VERSION_CODENAME")" stable" | \
  sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

Install docker

sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

Verify that Docker Compose is installed correctly by checking the version.

docker compose version

Set user permissions

Put the user in the docker group, so we don't need to add sudo to every docker command.

sudo groupadd docker

sudo usermod -aG docker $USER

newgrp docker

Logout and login to make this change permanent.

Install Nvidia Drivers

Do you have an NVIDIA GPU in your machine? Make sure you have the driver installed.

In Software & Updates > Additional Drivers > choose the latest NVIDIA driver.

Install Docker NVIDIA

Reference Manual

curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -

distribution=$(. /etc/os-release;echo $ID$VERSION_ID)

curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

sudo apt-get update

sudo apt-get install -y nvidia-docker2

sudo pkill -SIGHUP dockerd

sudo systemctl daemon-reload

sudo systemctl restart docker

Start the docker container

Run

./start_eurobin.sh

The script will enable x-forwarding for docker and perform docker compose up cram-eurobin, which will pull the image from DockerHub and launch it.

In your Terminal there should be a link. Paste it to your browser to open the Jupyter Notebook for CRAM.

cram_teaching's Issues

adjust assignment 7

it says

In the file "turtlesim-tf.lisp" write a function FOLLOW-TURTLE-IN-A-LOOP
which accepts 2 arguments: FOLLOWER-NAME and FOLLOWEE-NAME, which are turtle names,
e.g. the strings "turtle1" and "turtle2".
This function

initializes a new CL-TF:TRANSFORM-LISTENER and a new publisher
for turtle command velocities (see the SET-TURTLE-VELOCITY function from
assignment_6) that will send commands to the turtle called FOLLOWER-NAME.

but the function shouldn't init a new publisher, not a new transform listener

RLException: Unable to contact my own server

Fehlermeldung, wenn roscore gestartet wird:

RLException: Unable to contact my own server at [http://cyper:40771/].
This usually means that the network is not configured properly.
A common cause is that the machine cannot connect to itself.  Please check
for errors by running:
	ping cyper
For more tips, please see
	http://wiki.ros.org/ROS/NetworkSetup
The traceback for the exception was written to the log file

cyper ist der $HOSTNAME meines Laptops.

Was mir geholfen hat:

Starte den docker-Container mit HOSTNAME=localhost. Kann in die docker-compose-headless.yml unter environment eingefügt werden oder in das Image selber geschrieben werden.