自定义Keras图层失败

Question

我想要自定义Keras层，实现两个模型的输出分配不同的权重，并且权重可以如下训练

prediction1=model1.output
prediction2=model2.output
class WeightedSum(Layer):
    def __init__(self,**kwargs):
        super(WeightedSum, self).__init__(**kwargs)
    def build(self, input_shape):
        self.weights =K.variable(np.random.random(1))
        self.trainable_weights=[self.weights]
    def call(self, two_model_outputs):
        return self.weights * two_model_outputs[0] + (1 - self.weights) * two_model_outputs[1]
    def compute_output_shape(self, input_shape):
        return input_shape[0]
final_pred=WeightedSum()([prediction1,prediction2])

但我在写作上犯了一个错误，不知道该怎么做。

    Traceback (most recent call last):
      File "test-paper3.py", line 182, in <module>
        final_pred=WeightedSum()([prediction1,prediction2])
      File "/root/anaconda3/lib/python3.7/site-packages/keras/engine/base_layer.py", line 431, in __call__
        self.build(unpack_singleton(input_shapes))
      File "test-paper3.py", line 162, in build
        self.weights =K.variable(np.random.random(1))
    AttributeError: can't set attribute