class_docstr: A helper for use during training.  Only reads inputs.
  
  Returned sample_ids are the argmax of the RNN output logits.
class_docstr_tok: ["A","helper","for","use","during","training",".","Only","reads","inputs",".","Returned","sample_ids","are","the","argmax","of","the","RNN","output","logits","."]
code: def initialize(self, name=None):
      with ops.name_scope(name, "TrainingHelperInitialize"):
          finished = math_ops.equal(0, self._sequence_length)
          all_finished = math_ops.reduce_all(finished)
          next_inputs = control_flow_ops.cond(
              all_finished,
              lambda: self._zero_inputs,
              lambda: nest.map_structure(
                  lambda inp: inp.read(0), self._input_tas
              ),
          )
          return (finished, next_inputs)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import six
  from tensorflow.contrib.distributions.python.ops import bernoulli
  from tensorflow.contrib.distributions.python.ops import categorical
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.layers import base
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import embedding_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import tensor_array_ops
  from tensorflow.python.util import nest
  from seq2seq.contrib.seq2seq import decoder
label_desc: Use image node_id 3 for calling the TrainingHelper obj's underlying member method code with example usage: obj.initialize(name) and returns: finished,  next_inputs