code: def tf_custom_logcosh_loss(img1, img2):
      return tf.math.reduce_mean(tf.keras.losses.logcosh(img1, img2))
  
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 5 for calling a global function with example usage: tf_custom_logcosh_loss(img1, img2) and returns: tf