With an L-layer GAT network, features from L hops away can be propagated to the aspect target node.
given a node i with a hidden state h i l at layer l and the node's neighbours n[i] as well as their hidden states, a GAT updates the node's hidden state at layer l + 1 using multi-head attentions (Vaswani et al., 2017).