如何在Keras中向输入数据添加均匀分布的噪声？

import numpy as np
from keras.datasets import mnist

(x_train, _), (x_test, _) = mnist.load_data()

x_train = x_train.astype('float32') / 255.
x_test = x_test.astype('float32') / 255.

def add_uniform_noise(data, noise_factor):
    noise = np.random.uniform(low=0.0, high=noise_factor, size=data.shape)
    noisy_data = data + noise
    noisy_data = np.clip(noisy_data, 0., 1.)  # 将数据限制在0到1之间
    return noisy_data

noise_factor = 0.2  # 噪声因子，控制噪声的强度
x_train_noisy = add_uniform_noise(x_train, noise_factor)
x_test_noisy = add_uniform_noise(x_test, noise_factor)