从具有多个标签的Pandas数据框创建Tensorflow数据集？

import pandas as pd
import tensorflow as tf

data = {'特征1': [1, 2, 3, 4, 5],
        '特征2': [6, 7, 8, 9, 10],
        '标签1': ['A', 'B', 'A', 'B', 'A'],
        '标签2': ['X', 'Y', 'X', 'Y', 'X']}
df = pd.DataFrame(data)

label_mapping = {'A': 0, 'B': 1, 'X': 0, 'Y': 1}
df['标签1'] = df['标签1'].map(label_mapping)
df['标签2'] = df['标签2'].map(label_mapping)

feature_columns = [tf.feature_column.numeric_column('特征1'),
                   tf.feature_column.numeric_column('特征2')]
label_columns = [tf.feature_column.numeric_column('标签1'),
                 tf.feature_column.numeric_column('标签2')]
dataset = tf.data.Dataset.from_tensor_slices((dict(df[feature_columns]), dict(df[label_columns])))