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 sample(self, time, outputs, name=None, **unused_kwargs):
      with ops.name_scope(
          name, "TrainingHelperSample", [time, outputs]
      ):
          sample_ids = math_ops.cast(
              math_ops.argmax(outputs, axis=-1), dtypes.int32
          )
          return sample_ids
  
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 4 for calling the TrainingHelper obj's underlying member method code with example usage: obj.sample(time, outputs, name) and returns: sample_ids