The aim is to have flexibility in creating model MLCubes from GaNDLF models. The user can now provide a custom entrypoint script for the MLCube which can act as a wrapper around calling gandlf_run. The goal is to NOT rely on having data input folder containing a csv file. Using a custom script, the model author can build a csv file before calling gandlf_run.

Proposed Changes

• Modify gandlf_deploy to allow custom entrypoint scripts for model deploy (like what we have for metrics deploy)
• add CI tests for deploy ( model + metrics deploy) and running the resulting MLCubes.

Checklist

• I have read the CONTRIBUTING guide.
• My PR is based from the current GaNDLF master .
• Non-breaking change (does not break existing functionality): provide as many details as possible for any breaking change.
• Function/class source code documentation added/updated.
• Code has been blacked for style consistency.
• If applicable, version information has been updated in GANDLF/version.py.
• If adding a git submodule, add to list of exceptions for black styling in pyproject.toml file.
• Usage documentation has been updated, if appropriate.
• Tests added or modified to cover the changes; if coverage is reduced, please give explanation.
• If customized dependency installation is required (i.e., a separate pip install step is needed for PR to be functional), please ensure it is reflected in all the files that control the CI, namely: python-test.yml, and all docker files [1,2,3].