class XorNetwork:
def __init__(self, nTrain=1000, nInputs=2, nNeurCapas=(2, 3, 1)):
self.Network = NeuralNetwork(nInputs, nNeurCapas)
self.Inputs = []
self.Outputs = []
I1 = [0, 0]
I2 = [0, 1]
I3 = [1, 0]
I4 = [1, 1]
for i in range(nTrain):
self.Inputs.append(I1)
self.Inputs.append(I2)
self.Inputs.append(I3)
self.Inputs.append(I4)
self.Outputs.append([xor(I1[0], I1[1])])
self.Outputs.append([xor(I2[0], I2[1])])
self.Outputs.append([xor(I3[0], I3[1])])
self.Outputs.append([xor(I4[0], I4[1])])
self.Network.realTraining(self.Inputs, self.Outputs)
self.Network.feed([0, 0])
print(self.Network.getOutput())
