code: def _softmax(values):
      """Returns the softmax of `values`."""
      total = sum(math.exp(v) for v in values)
      return [math.exp(v) / (1e-20 + total) for v in values]
  
imports: import math
  import tensorflow
  from tensorflow_ranking.python import losses
  from tensorflow_ranking.python import losses_impl
label_desc: Use image node_id 5 for calling a global function with example usage: _softmax(values) and returns: unknown