middle1 = Layer(4) middle2 = Layer(3) output = OutputLayer([1, 1]) network = Network([inputs, middle1, middle2, output]) network.connect() #print("changing weight of {} to 0.3".format(middle1.neurons[0])) #middle1.neurons[0].outputs[0].update_weight(0.3) for _ in range(100): print("-----middle1-------") [print(x.inputs) for x in middle1.neurons] [print(x.outputs) for x in middle1.neurons] print("-----middle2-------") [print(x.inputs) for x in middle2.neurons] [print(x.outputs) for x in middle2.neurons] network.stimulate() network.backpropagate() print("-----middle1-------") [print(x.inputs) for x in middle1.neurons] [print(x.outputs) for x in middle1.neurons] print("-----middle2-------") [print(x.inputs) for x in middle2.neurons] [print(x.outputs) for x in middle2.neurons] [print(n.get_value()) for n in output.neurons]