Installation

Using pip

DeepINN can be installed via pip using the following command:

pip install DeepINN

Docker image

Pull the image with suitable tagname. The image is available here.

docker pull prakhars962/deepinn:tagname

CPU Only

The image opens a jupyter server by default.

docker run -p 8888:8888 prakhars962/deepinn:pre-release

You can override the jupyter server entrypoint using the following command.

docker run -it --entrypoint /bin/bash prakhars962/deepinn:pre-release

GPU passthrough

First install nvidia-docker using this guide.

Now run the container with nvidia-docker.

nvidia-docker run -it --entrypoint /bin/bash prakhars962/deepinn:pre-release

This command will bind the pwd to /workspace/tutorials and open a jupyter-lab with GPU support.

nvidia-docker run -v $(pwd):/workspace/tutorials -p 8888:8888  prakhars962/deepinn:pre-release

Alternatively, one can run interactive session.

nvidia-docker run -v $(pwd):/workspace/tutorials -it --entrypoint /bin/bash  prakhars962/deepinn:pre-release

Tagless copy

Each time you pull the updated image, docker will create a tagless copy of the old one.

╰─ docker images                              
REPOSITORY            TAG           IMAGE ID       CREATED             SIZE
prakhars962/deepinn   pre-release   886808706155   4 minutes ago       6.99GB
prakhars962/deepinn   <none>        0bb744f6159e   38 minutes ago      6.99GB
prakhars962/deepinn   <none>        4ffbb67f8447   About an hour ago   6.8GB
prakhars962/deepinn   <none>        fe16ca34f9d9   About an hour ago   6.8GB

The only solution is to delete them one by one using the IMAGE_ID.

docker image rm -f IMAGE_ID