When I debug the GAT model, I am a little confused by the dimensions of nodes.mailbox[‘e’], generally, it will be a 3-d tensor, anyone could explain the meaning of each dimension?
Here is a code demo from GAT tutorial:
def reduce_func(self, nodes):
# reduce UDF for equation (3) & (4)
# equation (3)
alpha = F.softmax(nodes.mailbox['e'], dim=1)
# equation (4)
h = torch.sum(alpha * nodes.mailbox['z'], dim=1)
return {'h': h}