I am new in use of tensoflow, so at the moment I wish to run sum code using the tokenizer function that calls a .lower() module on some texts, but the result is an attribute error as follows:

.vocabulary.update(tokenizer.tokenize(text.numpy().lower()))      
                                         ^^^^^^^^^^^^^^^^^^
AttributeError: 'numpy.ndarray' object has no attribute 'lower'      
PS C:UsersUSER>

Here is the bulk of my code which I expected to give a no error result

(ds_train, ds_test), ds_info = tfds.load(
    "mnist",
    split=["train", "test"],
    shuffle_files=True,
    as_supervised=True,
    with_info=True
)

def normalize_img(image, label):
    return tf.cast(image, tf.float32)/255.0, label

AUTOTUNE = tf.data.experimental.AUTOTUNE
BATCH_SIZE = 64

ds_train = ds_train.map(normalize_img, num_parallel_calls=AUTOTUNE)
ds_train = ds_train.cache()
ds_train = ds_train.shuffle(ds_info.splits["train"].num_examples)
ds_train = ds_train.batch(BATCH_SIZE)
ds_train = ds_train.prefetch(AUTOTUNE)

ds_test = ds_test.map(normalize_img, num_parallel_calls=AUTOTUNE)
de_test = ds_test.batch(128)
ds_test = ds_test.prefetch(AUTOTUNE)

model = keras.Sequential ([
    keras.Input(28, 28, 1),
    layers.Conv2D(32, 3, activation='relu', padding="same"),
    layers.Flatten(),
    layers.Dense(10),

])