def SKFF(self, inputs:list, reduction=8, name='SKFF'):
    with tf.variable_scope(name):
        ch_n=inputs[0].shape[3]
        num=len(inputs)
        d=max(ch_n//reduction, 4)
        
        inputs=tf.stack(inputs, 0)
        fea=tf.reduce_sum(inputs, 0)
        fea=tf.reduce_mean(fea, [1, 2], keep_dims=True)
        fea=self.conv_layer(fea, d, 1, name='du')
        fea=tf.keras.layers.PReLU()(fea)
        
        vecs=[self.conv_layer(fea, ch_n, 1, name=str(no)) for no in range(num)]
        vec=tf.concat(vecs,axis=1)
        weight=tf.nn.softmax(vec, axis=1)
        weight=tf.transpose(weight, (1, 0, 2, 3))
        weight=tf.expand_dims(weight, 2)
        out = inputs*weight
        out=tf.reduce_sum(out, 0)
        return out