How Graph Convolutional Neural Networks forward propagate?

Here we aggregate the information from the adjacent node and pass it to a neural network, then transform our own information and add them all.

But the main question is: how can we ensure that $$W_{k}(\sum(\frac{h_k}{N(V)})$$ will be the same size as $$B_{k}h_{v}$$ and does $$B_{k}$$ emply another neural network?