Creating custom connectivity in PyBrain neural networks

Question

I want to create an artificial neural network (in PyBrain) that follows the following layout:

However, I cannot find the proper way to achieve this. The only option that I see in the documentation is the way to create fully connected layers, which is not what I want: I want some of my input nodes to be connected to the second hidden layer and not to the first one.

Answer 1

The solution is to use the connection type of your choice, but with slicing parameters: inSliceFrom, inSliceTo, outSliceFrom and outSliceTo. I agree the documentation should mention this, so far it's only in the Connection class' comments.

Here is example code for your case:

#create network and modules net = FeedForwardNetwork() inp = LinearLayer(9) h1 = SigmoidLayer(2) h2 = TanhLayer(2) outp = LinearLayer(1) # add modules net.addOutputModule(outp) net.addInputModule(inp) net.addModule(h1) net.addModule(h2) # create connections net.addConnection(FullConnection(inp, h1, inSliceTo=6)) net.addConnection(FullConnection(inp, h2, inSliceFrom=6)) net.addConnection(FullConnection(h1, h2)) net.addConnection(FullConnection(h2, outp)) # finish up net.sortModules()