== Rancher Desktop
Download Rancher Desktop from https://rancherdesktop.io and open it on your local desktop. 

== Dockerhub Account
Create a Dockerhub account on https://hub.docker.com. You will also want to create a repository to push the custom images you build. Call it 'deepxde'

Remember to log in to your dockerhub account from your desktop. Enter `docker login` in your command line, and enter your password. You will only have to do this once. 

== Building Custom Image
Specifically for the DeepXDE package, you will need to create a folder on your local desktop, `deepxde`. Within this folder, create a dockerfile with `vim Dockerfile` and enter the following: 
{{{
FROM public.ecr.aws/j1r0q0g6/notebooks/notebook-servers/jupyter-tensorflow-cuda-full:v1.3.0-rc.1

USER root

RUN rm /etc/apt/sources.list.d/cuda.list
RUN rm /etc/apt/sources.list.d/nvidia-ml.list

RUN apt-get update && apt-get install -y --no-install-recommends imagemagick libopenmpi-dev \
 && apt-get clean \
 && rm -rf /var/lib/apt/lists/*

USER $NB_UID

# install - requirements.txt
COPY --chown=jovyan:users requirements.txt /tmp/requirements.txt
RUN python3 -m pip install -r /tmp/requirements.txt --quiet --no-cache-dir  -f \
 https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html \
 && rm -f /tmp/requirements.txt
}}}

Within the same `deepxde` folder on your local desktop, create a new file called `requirements.txt` by entering the following in command line: `vim requirements.txt`. Here are some packages you may want to include: 
{{{
ipython
numpy
scipy
tensorflow
scikit-learn
matplotlib
scikit-optimize
seaborn
tensorflow-probability
torch
torchvision
torchaudio
jax
flax
optax
paddlepaddle-gpu==2.4.2.post112
jupyter
jupyterlab
notebook
pandas
mpi4py
deepxde
mat73
}}}
You can add or remove the packages you need as required. 

Now, to build the custom image (for Mac), enter the following in your command line: `docker buildx build --platform linux/amd64 -t <username>/deepxde:<tagname> .`
You will need to use your dockerhub username and you can choose any tagname you want. For instance, your tagname could be `v1` for version 1 of the image you are building. 

== Pushing to Dockerhub
After building the image, push to Dockerhub: `docker push <username>/deepxde:<tagname>`

== Kubeflow
Go to the Notebooks tab and create a new server. Select `custom image` and enter `<username>/deepxde:<tagname>`. Choose the number of CPUs and GPUs (NVIDIA), also use your existing volume. Once this is done, you will want to launch the server!