ga.py 文件源码

def createModel(self, inputs, outputs, hiddenLayers, activationType):
        model = Sequential()
        if len(hiddenLayers) == 0: 
            model.add(Dense(self.output_size, input_shape=(self.input_size,), init='lecun_uniform'))
            model.add(Activation("linear"))
        else :
            model.add(Dense(hiddenLayers[0], input_shape=(self.input_size,), init='lecun_uniform'))
            if (activationType == "LeakyReLU") :
                model.add(LeakyReLU(alpha=0.01))
            else :
                model.add(Activation(activationType))

            for index in range(1, len(hiddenLayers)-1):
                layerSize = hiddenLayers[index]
                model.add(Dense(layerSize, init='lecun_uniform'))
                if (activationType == "LeakyReLU") :
                    model.add(LeakyReLU(alpha=0.01))
                else :
                    model.add(Activation(activationType))
            model.add(Dense(self.output_size, init='lecun_uniform'))
            model.add(Activation("linear"))
        optimizer = optimizers.RMSprop(lr=1, rho=0.9, epsilon=1e-06)
        model.compile(loss="mse", optimizer=optimizer)
        return model