Clone this repository. From your preferred directory execute:

git clone https://github.com/dhudsmith/manifold_learning.git

Install Docker on your machine. You can find installation instructions for various operating systems on the Docker website.

Once docker is installed, download the docker container image for this project by executing the command below from a terminal (current working directory does not matter). The docker images is very large, so this will take a while. Go make yourself a cup of coffee (or tea).

docker pull nvcr.io/nvidia/pytorch:19.06-py3

If operating on Windows, before testing your docker setup, go into Docker Settings->Shared Drives and click the checkbox next to the drive holding the cloned/downloaded code repository. A more detailed walkthrough can be found in this tutorial.

Test your docker setup by navigating into the manifold_learning directory that you cloned above and executing the following command:

sh run_docker_shell.sh

This command starts a bash terminal within the Docker environment. You should now be able to execute commands within the docker environment. Make sure that you can view the manifold_learning code.

You can exit docker with exit from the terminal.

Run your jupyter notebook server by navigating into the manifold_learning directory and executing the command below.

sh run_docker_jupyter.sh

This script internally spins up docker and hosts a jupyter notebook server which you can access via your browser at http://localhost:8888. Copy and paste the token from the command line output.

You can learn the basics of jupyter notebooks here: https://realpython.com/jupyter-notebook-introduction/. Use shift+enter to execute a cell.