Add ensemble of GNINA models

[RMeli]

Description

This PR adds the GNINAModelEnsemble class, which allow to combine different pre-trained GNINA models into a single class. Related to #33 and #35.

This PR also adds functions to easily load an ensemble of pre-trained models using their names, and to perform inference from the CLI. For the time being, the CLI requires a list of protein-ligand pairs in a file, instead of the protein and ligand directly as in GNINA.

The class assumes that the models perform both pose prediction and binding affinity prediction (which is the case for the pre-trained GNINA models, hence the GNINA name). A less strict class to be used with custom models (pose prediction only, or pose and flexible residues) will follow.

The dense model is not yet available since it appears to be problematic and it is under investigation. This means that the GNINA default model is not yet available.

PR Checklist

• Tests
• Documentation

[codecov]

Codecov Report

Merging #38 (1e9038d) into main (90fa1a7) will decrease coverage by 0.02%.
The diff coverage is 95.45%.