Hello, I have some confusion about the “aggregate operation” implementation in LGNN tutorial and recommended implementation, in the original paper, the part of the original paper that involves aggregate operation is \sum^{J-1}_{j=0}(A^{2^{j}}x^{k})_{i}, and the implementation of dgl is as follows:

```
def aggregate(self, g, z):
z_list = []
g.ndata['z'] = z
g.update_all(fn.copy_src(src='z', out='m'), fn.sum(msg='m', out='z'))
z_list.append(g.ndata['z'])
for i in range(self.radius - 1):
for j in range(2 ** i):
g.update_all(fn.copy_src(src='z', out='m'), fn.sum(msg='m', out='z'))
z_list.append(g.ndata['z'])
return z_list
```

for radius=3, it seems that above implementation only performs 4 message passing(1 out the loop, 3 in the loop).However, we can get A, A^2, A^4 according to the original paper for J = 3(J is equivalent to radius), and we need to perform 7(1+2+4) message passing. Should it be changed to the following?

```
def aggregate(self, g, z):
z_list = []
g.ndata['z'] = z
for i in range(self.radius):
for j in range(2 ** i):
g.update_all(fn.copy_src(src='z', out='m'), fn.sum(msg='m', out='z'))
z_list.append(g.ndata['z'])
return z_list
```

Is there something wrong with my understanding?

Thanks in advance!