class_docstr: A single training/test example for the Squad dataset.
  For examples without an answer, the start and end position are -1.
class_docstr_tok: ["A","single","training\/test","example","for","the","Squad","dataset",".","For","examples","without","an","answer",",","the","start","and","end","position","are","-1","."]
code: def __repr__(self):
      s = ""
      s += "qas_id: %s" % (self.qas_id)
      s += ", question_text: %s" % (self.question_text)
      s += ", doc_tokens: [%s]" % (" ".join(self.doc_tokens))
      if self.start_position:
          s += ", start_position: %d" % (self.start_position)
      if self.end_position:
          s += ", end_position: %d" % (self.end_position)
      if self.is_impossible:
          s += ", is_impossible: %r" % (self.is_impossible)
      return s
  
imports: import json
  import os
  import torch
  from pathlib import Path
  import pickle
  import logging
  import collections
  from io import open
  import shutil
  from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
  from torch.utils.data.distributed import DistributedSampler
  from transformers.tokenization_bert import BasicTokenizer, whitespace_tokenize
  from transformers import WEIGHTS_NAME, BertTokenizer, XLNetTokenizer, DistilBertTokenizer
label_desc: Use image node_id 3 for calling the QAExample obj's underlying member method code with example usage: obj.__repr__() and returns: s