Hi, I have two questions w.r.t
Pm_Pd implemented in DGL-LGNN. I read the original paper, and think the matrices
pd should be the forms in this link, respectively. So what the form is
DGL since it is loaded from a pickel file in the source code?
Another question is in
def forward(self, g, lg, pm_pd):
pm_pd is shown directly to
forward method rather than computed in the feed forward process, then
pm_pd should be batched before training. We can view a batched graph as several unlinked graphs, however as an example, when batch process
pm, it seems each
pm of the unlinked graphs should be a block in the huge matrix, which could be implemented with
torch.block_diag. Finally the batched
Pm matrix is a block matrix. Is that right?