code: def scale_loss_for_distribution(loss_value):
      """Scales and returns the given loss value by the number of replicas."""
      num_replicas = distribute_lib.get_strategy().num_replicas_in_sync
      if num_replicas > 1:
          loss_value *= 1.0 / num_replicas
      return loss_value
  
imports: from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import keras_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
label_desc: Use image node_id 7 for calling a global function with example usage: scale_loss_for_distribution(loss_value) and returns: loss_value