def img_random_contrast(img):
    return  tf.image.random_contrast(img, 0.95,1 )

test_random_contrast = (train_data.map(lambda img, label: img_random_contrast(img)))
for img in test_random_contrast.take(1):
    for num in range(16):
        ax = plt.subplot(4,4,num+1)
        plt.imshow((img[num].numpy()).astype("uint8"))
        plt.axis("off")  
plt.suptitle("Random Contrast")
plt.tight_layout()
plt.show()

        __
        __