class_docstr: Input data structure of BERT/ERNIE, can satisfy single sequence task like
  text classification, sequence lableing; Sequence pair task like dialog
  task.
  
  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.
code: def __init__(self, guid, text_a, text_b=None, label=None):
      self.guid = guid
      self.text_a = text_a
      self.text_b = text_b
      self.label = label
  
imports: import os
  from paddlehub.utils.log import logger
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)