Migrate the ethos of TypeDB-ML to be a library to support machine learning using existing graph learning frameworks, starting with support for PyTorch Geometric and NetworkX to support in-memory graphs and general-purpose graph algorithms.
What are the changes implemented in this PR?
Encoding of a TypeDB graph (already exported into NetworkX) into a PyTorch Geometric HeteroData object
Updating the Diagnosis example to demonstrate how to create a GNN using TypeDB, TypeDB-ML and PyTorch Geometric
Approved for the build only. The API contains many changes and most of them are fundamental. They will be reviewed later in a longer discussion (most probably in person) with James and Joshua.
What is the goal of this PR?
Migrate the ethos of TypeDB-ML to be a library to support machine learning using existing graph learning frameworks, starting with support for PyTorch Geometric and NetworkX to support in-memory graphs and general-purpose graph algorithms.
What are the changes implemented in this PR?
Solves #44