Tensorflow模型子类化多输入

import tensorflow as tf
from tensorflow import keras

class MultiInputModel(tf.keras.Model):
    def __init__(self):
        super(MultiInputModel, self).__init__()
        self.dense1 = keras.layers.Dense(64, activation='relu')
        self.dense2 = keras.layers.Dense(64, activation='relu')
        self.dense3 = keras.layers.Dense(10, activation='softmax')

    def call(self, inputs):
        input1, input2 = inputs
        x1 = self.dense1(input1)
        x2 = self.dense2(input2)
        concatenated = tf.concat([x1, x2], axis=-1)
        output = self.dense3(concatenated)
        return output

# 创建模型实例
model = MultiInputModel()

# 编译模型
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])

# 训练模型
model.fit([input1, input2], labels, epochs=10, batch_size=32)