code: def softmax(self, input, name):
      fluid = import_fluid()
      shape = input.shape
      if len(shape) > 2:
          for sz in shape[2:]:
              assert sz == 1, "invalid input shape[%s] for softmax" % (
                  str(shape)
              )
          input = fluid.layers.reshape(input, shape[0:2])
  
      output = fluid.layers.softmax(
          input, name=self.get_unique_output_name(name, "softmax")
      )
      return output
  
imports: from __future__ import print_function
  from builtins import str
  from past.builtins import basestring
  from builtins import object
  import sys
  import os
  import math
  import numpy
label_desc: Use image node_id 23 for calling the Network obj's underlying member method code with example usage: obj.softmax(input, name) and returns: output