def prepare_dataset():
    mnist = keras.datasets.mnist
    ((train_images, train_labels), (test_images, test_labels)) = mnist.load_data()
    train_images = (train_images / 255.0)
    test_images = (test_images / 255.0)
    return (train_images, train_labels)
def prepare_dataset():
    mnist = keras.datasets.mnist
    ((train_images, train_labels), (test_images, test_labels)) = mnist.load_data()
    train_images = (train_images / 255.0)
    test_images = (test_images / 255.0)
    return (train_images, train_labels)