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]
