如何在Call()方法中保存带有位置参数的keras子类模型？

import tensorflow as tf
from tensorflow import keras

class MyModel(keras.Model):
    def __init__(self, num_classes):
        super(MyModel, self).__init__()
        self.num_classes = num_classes
        self.dense = keras.layers.Dense(num_classes, activation='softmax')

    def call(self, inputs, training=False, mask=None):
        x, y = inputs  # 位置参数
        # 模型的前向传播逻辑
        x = self.dense(x)
        return x + y

# 创建模型实例
model = MyModel(num_classes=10)

# 构造输入数据
x = tf.ones((1, 10))
y = tf.ones((1, 10))

# 调用模型
output = model.call((x, y))

# 保存模型
concrete_func = model.call.get_concrete_function((x, y))
tf.saved_model.save(model, 'saved_model', signatures=concrete_func)