def main():
topology = []
topology.append(2)
topology.append(3)
topology.append(3)
topology.append(1)
net = Network(topology)
neuron.eta = 0.09
neuron.alpha = 0.015
inputs = [[0, 0], [0, 1], [1, 0], [1, 1]]
outputs = [[0], [1], [1], [0]]
while True:
err = 0
for i in range(len(inputs)):
net.setInput(inputs[i])
net.feedForward()
net.backPropagate(outputs[i])
err = err + net.getError(outputs[i])
print("Error: ", err)
if err < 1.5:
break
while True:
a = int(input("First input: "))
b = int(input("Second input: "))
net.setInput([a, b])
net.feedForward()
print(net.getThResults())
def main():
result_list = [[None], [None]]
topology = []
topology.append(2)
topology.append(3)
topology.append(3)
topology.append(1)
net1 = Network(topology)
net2 = Network(topology)
neuron.eta = 0.09
neuron.alpha = 0.015
inputs1 = [[0, 0], [0, 1]]
outputs1 = [[0], [1]]
inputs2 = [[1, 0], [1, 1]]
outputs2 = [[1], [0]]
threads = []
nets = [net1, net2]
outputs = [outputs1, outputs2]
inputs = [inputs1, inputs2]
for i in range(2):
t = threading.Thread(target=TrainNet,
args=(inputs[i], [nets[i]], outputs[i], i,
result_list))
threads.append(t)
t.start()
for i in range(2):
threads[i].join()
net1 = result_list[0]
net2 = result_list[1]
while True:
a = int(input("First input: "))
b = int(input("Second input: "))
if (a > 0):
net2.setInput([a, b])
net2.feedForward()
print(net1.getThResults())
else:
net1.setInput([a, b])
net1.feedForward()
print(net1.getThResults())
