code: def postprocess(x, n_bits_x=8):
    
    x = tf.where(tf.is_finite(x), x, tf.ones_like(x))
    x = tf.clip_by_value(x, -0.5, 0.5)
    x += 0.5
    x = x * 2**n_bits_x
    return tf.cast(tf.clip_by_value(x, 0, 255), dtype=tf.uint8)
docs: Converts x from [-0.5, 0.5], to [0, 255].
  
    Args:
      x: 3-D or 4-D Tensor normalized between [-0.5, 0.5]
      n_bits_x: Number of bits representing each pixel of the output.
                Defaults to 8, to default to 256 possible values.
    Returns:
      x: 3-D or 4-D Tensor representing images or videos.