code: def input_diff(orig_img):
      """Average L2 difference between optimized image and orig_img.
  
      This objective is usually mutliplied by a negative number and used as a
      penalty in making advarsarial counterexamples.
      """
  
      def inner(T):
          diff = T("input") - orig_img
          return tf.sqrt(tf.reduce_mean(diff**2))
  
      return inner
  
imports: from __future__ import absolute_import, division, print_function
  from decorator import decorator
  import numpy
  import tensorflow
  from lucid.optvis.objectives_util import _dot, _dot_cossim, _extract_act_pos, _make_arg_str, _T_force_NHWC, _T_handle_batch
label_desc: Use image node_id 19 for calling a global function with example usage: input_diff(orig_img) and returns: inner, tf