code: def categorical_crossentropy(y_true, y_pred):
      batch_size = y_true.shape.as_list()[0]
      batch_size_inv = 1 / batch_size
      out = -y_true * tfe.log(y_pred)
      cce = out.reduce_sum() * batch_size_inv
      return cce
  
imports: import tf_encrypted
label_desc: Use image node_id 4 for calling a global function with example usage: categorical_crossentropy(y_true, y_pred) and returns: cce