Combining textual and numeric features into pre-trained Transformer BERT
When they are talking about aggregating their outputs, they mean the final embeddings (just before the classification layer) not the output of the network itself.
You take the embeddings from both of the networks and concatenate them vertically. This concatenated embedding you use to predict the final output you wanted.
Torch has a function torch.cat for this purpose.