Regarding examples/ppi.py

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Hello,
I'm new to GNN and currently interested in learning GAT for multilabel classification. Out of many source codes, I found an example of GAT on the PPI dataset, /examples/ppi.py, which has a different architecture than I found mostly. E.g. while defining the forward propagation, why torch.nn.linear is used and later added to GAT inside elu()?
(The link is: https://github.com/pyg-team/pytorch_geometric/blob/master/examples/ppi.py)

Please elaborate on how this GAT structure and functioning differ from typical GAT applications.
Could you share the relevant reference/documentation, if available?