code: def softmax(x):
      """Compute softmax values for each sets of scores in x."""
      e_x = np.exp(x - np.max(x))
      return e_x / e_x.sum(axis=0)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import random
  from magenta.contrib import training
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling a global function with example usage: softmax(x) and returns: unknown