Pre-processing the dataset download using tfds.load()

preprocess_dataset.py

def format_example(image, label):
    image = tf.cast(image, tf.float32)
    # Normalize the pixel values
    image = image / 255.0
    # Resize the image
    image = tf.image.resize(image, (IMG_SIZE, IMG_SIZE))
    return image, label

train = raw_train.map(format_example)
validation = raw_validation.map(format_example)
test = raw_test.map(format_example)

Thank u

Its worth to mention that you should load your dataset with tfds.load(..., as_supervised=True)