keras 模型中自定义上采样函数，加载模型报错: ValueError: Unknown layer: BilinearUpsampling

模型自定义了BilinearUpsampling层如下代码，模型训练能正常调用BilinearUpsampling，模型保存用ModelCheckpoint，测试时加载模型报错：ValueError: Unknown layer: BilinearUpsampling

class BilinearUpsampling(Layer):

    def __init__(self, upsampling=(2, 2), data_format=None, **kwargs):

        super(BilinearUpsampling, self).__init__(**kwargs)
        self.data_format = conv_utils.normalize_data_format(data_format)
        self.upsampling = conv_utils.normalize_tuple(upsampling, 2, 'size')
        self.input_spec = InputSpec(ndim=4)

    def compute_output_shape(self, input_shape):
        height = self.upsampling[0] * \
            input_shape[1] if input_shape[1] is not None else None
        width = self.upsampling[1] * \
            input_shape[2] if input_shape[2] is not None else None
        return (input_shape[0],
                height,
                width,
                input_shape[3])

    def call(self, inputs):
        return K.tf.image.resize_bilinear(inputs, (int(inputs.shape[1]*self.upsampling[0]),
                                                   int(inputs.shape[2]*self.upsampling[1])))

    def get_config(self):
        config = {'size': self.upsampling,
                  'data_format': self.data_format}
        base_config = super(BilinearUpsampling, self).get_config()
        return dict(list(base_config.items()) + list(config.items()))