问NoneType‘object没有属性'_inbound_nodes’

EN

def sliced(x,expert_num):
    return x[:,:,:expert_num]

def reduce(x, axis):
    return K.sum(x, axis=axis, keepdims=True)

def gatExpertLayer(inputGate, inputExpert, expert_num, nb_class):
    #expert_num=30
    #nb_class=10
    input_vector1 = Input(shape=(inputGate.shape[1:]))
    input_vector2 = Input(shape=(inputExpert.shape[1:]))

    #The gate
    gate = Dense(expert_num*nb_class, activation='softmax')(input_vector1)
    gate = Reshape((1,nb_class, expert_num))(gate)
    gate = Lambda(sliced, output_shape=(nb_class, expert_num), arguments={'expert_num':expert_num})(gate)

    #The expert
    expert = Dense(nb_class*expert_num, activation='sigmoid')(input_vector2)
    expert = Reshape((nb_class, expert_num))(expert)

    #The output
    output = tf.multiply(gate, expert)
    #output = keras.layers.merge([gate, expert], mode='mul')
    output = Lambda(reduce, output_shape=(nb_class,), arguments={'axis': 2})(output)

    model = Model(input=[input_vector1, input_vector2], output=output)

    model.compile(loss='mean_squared_error', metrics=['mse'], optimizer='adam')

    return model