This module contains utility functions for neural knowledge graph embedding models.

Saving/Restoring Models

Models can be saved and restored from disk. This is useful to avoid re-training a model.

save_model(model[, model_name_path, protocol]) Save a trained model to disk.
restore_model([model_name_path]) Restore a saved model from disk.


Functions to visualize embeddings.

create_tensorboard_visualizations(model, loc) Export embeddings to Tensorboard.


Function to convert a pandas DataFrame with headers into triples.

dataframe_to_triples(X, schema) Convert DataFrame into triple format.