code: def preprocess_for_eval(image, image_size=224, normalize=True):
    
    if normalize: image = tf.to_float(image) / 255.0
    image = _do_scale(image, image_size + 32)
    if normalize: image = _normalize(image)
    image = _center_crop(image, image_size)
    image = tf.reshape(image, [image_size, image_size, 3])
    return image
docs: Preprocesses the given image for evaluation.
  
    Args:
      image: `Tensor` representing an image of arbitrary size.
      image_size: int, how large the output image should be.
      normalize: bool, if True the image is normalized.
  
    Returns:
      A preprocessed image `Tensor`.