如何加载Tensorflow数据集"Iris“并将标签更改为one-hot编码

import tensorflow as tf
from sklearn.preprocessing import OneHotEncoder

iris = tf.keras.datasets.iris
(x_train, y_train), (x_test, y_test) = iris.load_data()

encoder = OneHotEncoder(sparse=False)
y_train = encoder.fit_transform(y_train.reshape(-1, 1))
y_test = encoder.transform(y_test.reshape(-1, 1))

print("训练集维度：", x_train.shape)
print("训练集标签维度：", y_train.shape)
print("测试集维度：", x_test.shape)
print("测试集标签维度：", y_test.shape)

import tensorflow as tf
from sklearn.preprocessing import OneHotEncoder

# 加载"Iris"数据集
iris = tf.keras.datasets.iris
(x_train, y_train), (x_test, y_test) = iris.load_data()

# 将标签进行one-hot编码
encoder = OneHotEncoder(sparse=False)
y_train = encoder.fit_transform(y_train.reshape(-1, 1))
y_test = encoder.transform(y_test.reshape(-1, 1))

# 打印数据集的维度信息
print("训练集维度：", x_train.shape)
print("训练集标签维度：", y_train.shape)
print("测试集维度：", x_test.shape)
print("测试集标签维度：", y_test.shape)