code: def get_loss_fn(loss_factor=1.0):
      """Returns loss function for BERT pretraining."""
  
      def _bert_pretrain_loss_fn(unused_labels, losses, **unused_args):
          return tf.keras.backend.mean(losses) * loss_factor
  
      return _bert_pretrain_loss_fn
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import yaml
  import os
  import sys
  import tensorflow
  from absl import app
  from absl import flags
  from absl import logging
  from utils.logs import logger
  from utils.misc import keras_utils
  from utils import bert_modeling
  from utils import bert_models
  from utils import common_flags
  from utils import input_pipeline
  from utils import bert_utils
  from autodist import AutoDist
  from autodist.strategy.all_reduce_strategy import AllReduce
  from autodist.strategy.ps_strategy import PS
  from autodist.strategy.ps_lb_strategy import PSLoadBalancing
  from autodist.strategy.parallax_strategy import Parallax
  from autodist.strategy.partitioned_ps_strategy import PartitionedPS
label_desc: Use image node_id 2 for calling a global function with example usage: get_loss_fn(loss_factor) and returns: _bert_pretrain_loss_fn, unknown