class_docstr: A single training/test example for simple sequence classification.
class_docstr_tok: ["A","single","training\/test","example","for","simple","sequence","classification","."]
docstr: Constructs a InputExample.
  
  Args:
    guid: Unique id for the example.
    text_a: string. The untokenized text of the first sequence. For single
      sequence tasks, only this sequence must be specified.
    text_b: (Optional) string. The untokenized text of the second sequence.
      Only must be specified for sequence pair tasks.
    label: (Optional) string. The label of the example. This should be
      specified for train and dev examples, but not for test examples.
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code: def __init__(self, guid, text_a, text_b=None, label=None):
      """Constructs a InputExample.
  
      Args:
        guid: Unique id for the example.
        text_a: string. The untokenized text of the first sequence. For single
          sequence tasks, only this sequence must be specified.
        text_b: (Optional) string. The untokenized text of the second sequence.
          Only must be specified for sequence pair tasks.
        label: (Optional) string. The label of the example. This should be
          specified for train and dev examples, but not for test examples.
      """
      self.guid = guid
      self.text_a = text_a
      self.text_b = text_b
      self.label = label
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import csv
  import os
  import mesh_tensorflow
  import mesh_tensorflow.bert.bert
  import mesh_tensorflow.bert.optimization
  import mesh_tensorflow.bert.tokenization
  from six.moves import range
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 1 to create a new InputExample object from inherited base classes: object with example: obj = InputExample(guid, text_a, text_b, label)