8.2.9 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:

• JShell
• Java
• Python

opg4j> var vertexVectors = model.inferEmbeddings(fullGraph, testVertices).flattenAll()
opg4j> vertexVectors.write().
    db().
    name("vertex vectors").
    tablename("vertexVectors").  
    overwrite(true).             
    store()

PgxFrame vertexVectors = model.inferEmbeddings(fullGraph,testVertices).flattenAll();
vertexVectors.write()
    .db()
    .name("vertex vectors")
    .tablename("vertexVectors") 
    .overwrite(true)            
    .store();

vertex_vectors = model.infer_embeddings(full_graph, test_vertices).flatten_all()
vertex_vectors.write().db().table_name("table_name").name("vertex_vectors").overwrite(True).store()

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