code: def ld_mnist():
    
  
    def convert_types(image, label):
      image = tf.cast(image, tf.float32)
      image /= 255
      return image, label
  
    dataset, info = tfds.load('mnist', data_dir='gs://tfds-data/datasets', with_info=True,
                              as_supervised=True)
    mnist_train, mnist_test = dataset['train'], dataset['test']
    mnist_train = mnist_train.map(convert_types).shuffle(10000).batch(128)
    mnist_test = mnist_test.map(convert_types).batch(128)
    return EasyDict(train=mnist_train, test=mnist_test)
docs: Load training and test data.