AI Modules

AI Modules are git-based repositories to store your ML function. These are either Models or Data Operations (Data Ops) or Data Visualizations.

The idea is that each AI Module in the AI Library hosts a specific and atomic function. This way, you and your team (or the entire community) can use this script freely and project unbound within the built-in datapipelines within the ML projects (the other tab in the dashboard).

For example: You might create a code project just to rotate images. Or, you just create a new model (algorithm) that you want to share.

You can create new code projects using the dashboard view when selecting the corresponding card. Remember to set the visibility level according to your objective (as these will be passed on to the published code modules)

Please keep in mind that you need to publish your code project before it is discoverable and usable within the data-pipelines!

Publishing a code project

Publishing a code project will containerize your script with all required packages and environment variables and make your function discoverable and usable within the data pipelines in MLReef. Use a model repository to publish a new model (or algorithm) that then can be found and used in the experiment section within a ML project.

We call a published code repository a code module, as these are modules then you or your team can use atomically in the data pipelines.

In your code repository you will find a publishing wizard (accessible via the publish button). Follow these instructions to start an automatic publishing pipeline to publish your code.

In order to publish, you will need the following files placed in your master branch in your code project:

  • Use at least one python file that serves as an entry point for your ML function. This python file should contain the parameter annotations to make the parameter adjustable later on.
  • You will also need a requirement.txt file (named exactly reuirement.txt) that describes the libraries (packages) your script requires. Please do not forget to include the version, for example by adding ==1.0 after the package.

If your code project (repository) is set to private, the usable code module in the data pipelines will inherit this setting. If you only have access to the code repository, then you will only be able to view and use it.

To view all details on how to publish a code repository, visit this section: publishing a code project