code: def loss_logistic(outputs, y):
      margins = -y * tf.transpose(outputs)
      raw_loss = tf.log(tf.add(1.0, tf.exp(margins)))
      return tf.minimum(raw_loss, 100, name="truncated_log_loss")
  
file_path: tffm/tffm/utils.py
imports: import math
  import numpy
  import tensorflow
  import itertools
  from itertools import combinations_with_replacement, takewhile, count
  from collections import defaultdict
label_desc: Use image node_id 9 for calling a global function with example usage: loss_logistic(outputs, y) and returns: tf