title: Should I still normalize image data (divide by 255) before using per_image_standardization?
body: <p>When using Tensorflow and loading image data I currently have:</p>
  
  <pre><code>image = tf.io.decode_png(tf.io.read_file(path), channels=3)
  image = tf.reshape(image, [84, 84, 3])
  image = tf.cast(image, tf.float32)
  return image / 255.0
  </code></pre>
  
  <p>But, I want to use <code>tf.per_imdage_standardization</code>, should I keep the division by 255 or does it become not needed anymore?</p>