8.2.8 Inferring Embeddings for a Supervised GraphWise Model

You can use a trained model to infer embeddings for unseen nodes and store in the database as described in the following code:

Inferring Embeddings Using JShell

opg4j> var vertexVectors = model.inferEmbeddings(fullGraph, fullGraph.getVertices()).flattenAll();
opg4j> vertexVectors.write().
    db().
    name("vertex vectors").
    tablename("vertexVectors").  // indicate the name of the table in which the data should be stored
    overwrite(true).             // indicate that if there is a table with the same name, it will be overwritten (truncated)
    store();

Inferring Embeddings Using Java

PgxFrame vertexVectors = model.inferEmbeddings(fullGraph,fullGraph.getVertices()).flattenAll();
vertexVectors.write()
    .db()
    .name("vertex vectors")
    .tablename("vertexVectors") // indicate the name of the table in which the data should be stored
    .overwrite(true)            // indicate that if there is a table with the same name, it will be overwritten (truncated)
    .store();

Inferring Embeddings Using Python

vertex_vectors = model.infer_embeddings(full_graph, full_graph.get_vertices()).flatten_all()
vertexVectors.write().db(name="vertex vectors", "tablename", overwrite=True)

The schema for the vertexVectors will be as follows without flattening (flattenAll splits the vector column into separate double-valued columns):

+---------------------------------------------------------------+
| vertexId                                | embedding           |
+---------------------------------------------------------------+

Note:

All the preceding examples assume that you are inferring the embeddings for a model in the current logged in database. If you must infer embeddings for the model in a different database then refer to the examples in Inferring Embeddings for a Model in Another Database.

• Inferring Embeddings for a Model in Another Database