from typing import Optional

import tensorflow as tf
import matplotlib.pyplot as plt


def visualize_data(dataset: tf.data.Dataset, data_augmentation: Optional[tf.keras.Sequential]=None) -> None:
    plt.figure(figsize=(10, 10))
    for images, labels in dataset.take(1):
        for i in range(9):
            _ = plt.subplot(3, 3, i + 1)
            
            if data_augmentation != None:
                augmented_image = data_augmentation(images)
                plt.imshow(augmented_image[0].numpy().astype('uint8'))
            else:
                plt.imshow(images[i].numpy().astype('uint8'))
            
            plt.title(int(labels[i]))
            plt.axis('off')
    plt.show()