AI4OS Development Environment
This is a Docker image for developing new modules
Model
Published by
DEEP-Hybrid-DataCloud Consortium
Created:
- Updated:
Model Description
This is a Docker image for developing new modules. It comes preinstalled with DEEPaaS, JupyterLab or VSCode, Tensorflow or PyTorch, and a number of other tools (see here) As you have access to the terminal of JupyterLab or VSCode, you can develop and debug your application, add your preferred tools.
Test this module
You can test and execute this module in various ways.
Excecute locally on your computer using Docker
You can run this module directly on your computer, assuming that you have Docker installed, by following these steps:
$ docker pull deephdc/deep-oc-generic-dev
$ docker run -ti -p 5000:5000 deephdc/deep-oc-generic-devExecute on your computer using udocker
If you do not have Docker available or you do not want to install it, you can use udocker within a Python virtualenv:
$ virtualenv udocker
$ source udocker/bin/activate
(udocker) $ pip install udocker
(udocker) $ udocker pull deephdc/deep-oc-generic-dev
(udocker) $ udocker create deephdc/deep-oc-generic-dev
(udocker) $ udocker run -p 5000:5000 deephdc/deep-oc-generic-dev
In either case, once the module is running, point your browser to
http://127.0.0.1:5000/ and you will see the API
documentation, where you can test the module functionality, as well as
perform other actions (such as training).
For more information, refer to the user documentation.