如何为接受各种形状的多个输入的`tf.keras`模型创建`tf.data.Dataset`？

import tensorflow as tf

image_paths = [...]  # 图像文件路径列表
text_data = [...]  # 文本数据列表

image_dataset = tf.data.Dataset.from_tensor_slices(image_paths)
text_dataset = tf.data.Dataset.from_tensor_slices(text_data)

def preprocess_image(image_path):
    # 加载图像文件并进行预处理
    image = tf.io.read_file(image_path)
    image = tf.image.decode_image(image, channels=3)
    image = tf.image.resize(image, [224, 224])
    image = image / 255.0  # 归一化
    return image

def preprocess_text(text):
    # 文本处理
    # ...

image_dataset = image_dataset.map(preprocess_image)
text_dataset = text_dataset.map(preprocess_text)

dataset = tf.data.Dataset.zip((image_dataset, text_dataset))

dataset = dataset.shuffle(buffer_size=1000)
dataset = dataset.batch(batch_size=32)