Hi all,
as the headline suggests, I want to train a model for graph classification using Pytorch-geometric.
As a matter of fact, I actually have many samples based on the same graph structure, differing in their node features (one node-feature vector per sample).
I tried to create a data object for each sample (referring to it as a different presentation of the same graph), but that is very computationally expensive, because there are relatively many such samples.
Therefore, I’m looking for a way to do graph-level classification, with a batching system that will refer to all graphs as having the same nodes, and the same number of node features.
Is that possible?
Thanks!