如何为字符串列正确使用tensorflow数据集映射函数

import tensorflow as tf

string_column = tf.feature_column.categorical_column_with_vocabulary_list(
    key='string_feature',
    vocabulary_list=['value1', 'value2', 'value3']
)

def map_string_feature(string_feature):
    # 对字符串进行处理的逻辑
    # 返回处理后的结果
    return processed_string_feature

feature_columns = [
    tf.feature_column.embedding_column(string_column, dimension=10)
]

def map_features(features):
    # 获取字符串列的值
    string_feature = features['string_feature']
    # 调用映射函数处理字符串列
    processed_string_feature = map_string_feature(string_feature)
    # 更新特征字典
    features['string_feature'] = processed_string_feature
    return features

dataset = tf.data.Dataset.from_tensor_slices((features, labels))
dataset = dataset.map(map_features)