code: def _sigmoid_cross_entropy(labels, logits):
      def per_position_loss(logit, label):
          return (
              max(logit, 0)
              - logit * label
              + math.log(1 + math.exp(-abs(logit)))
          )
  
      return sum(
          per_position_loss(logit, label)
          for label, logit in zip(labels, logits)
      )
  
imports: import math
  import tensorflow
  from tensorflow_ranking.python import losses
  from tensorflow_ranking.python import losses_impl
label_desc: Use image node_id 6 for calling a global function with example usage: _sigmoid_cross_entropy(labels, logits) and returns: sum, unknown