code: def tf_custom_adaptive_rgb_loss(a, b):
      from adaptive import image_lossfun
  
      loss, _, _ = image_lossfun(
          b - a, color_space="RGB", representation="PIXEL"
      )
      return tf.math.reduce_mean(loss)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import tensorflow
  import bz2
  import PIL.Image
  from PIL import ImageFilter
  import numpy
  from keras.models import Model
  from keras.applications.vgg16 import VGG16, preprocess_input
  import keras.backend
  import traceback
  import external.stylegan2.dnnlib.tflib
  from core.landmark_handler import Landmark_Handler
  from core import arcface_handler
label_desc: Use image node_id 3 for calling a global function with example usage: tf_custom_adaptive_rgb_loss(a, b) and returns: tf