class_docstr: A single training/test example for token classification.
docstr: Constructs a InputExample.
  
  Args:
      guid: Unique id for the example.
      words: list. The words of the sequence.
      labels: (Optional) list. The labels for each word of the sequence. This should be
      specified for train and dev examples, but not for test examples.
      trigger_word_ids: set token_type_ids of trigger tokens to 1, used in argument extraction task
docstr_tok: ["Constructs","a","InputExample",".","Args",":","guid",":","Unique","id","for","the","example",".","words",":","list",".","The","words","of","the","sequence",".","labels",":","(","Optional",")","list",".","The","labels","for","each","word","of","the","sequence",".","This","should","be","specified","for","train","and","dev","examples",",","but","not","for","test","examples",".","trigger_word_ids",":","set","token_type_ids","of","trigger","tokens","to","1",",","used","in","argument","extraction","task"]
code: def __init__(self, guid, words, labels, trigger_word_ids):
      """Constructs a InputExample.
  
      Args:
          guid: Unique id for the example.
          words: list. The words of the sequence.
          labels: (Optional) list. The labels for each word of the sequence. This should be
          specified for train and dev examples, but not for test examples.
          trigger_word_ids: set token_type_ids of trigger tokens to 1, used in argument extraction task
      """
      self.guid = guid
      self.words = words
      self.labels = labels
      self.trigger_word_ids = trigger_word_ids
  
imports: from __future__ import absolute_import, division, print_function
  import json
  import logging
  import os
  import sys
  from copy import deepcopy
  from io import open
  from transformers import XLMRobertaTokenizer, BertTokenizer, RobertaTokenizer, AutoTokenizer
  from .utils_ee import read_by_lines, write_by_lines, load_dict, label_data, process_remained_pred_trigger, clear_wrong_tokens
  from torch.nn.utils.rnn import pad_sequence
  from tqdm import tqdm
label_desc: Use image node_id 1 to create a new InputExample object from inherited base classes: object with example: obj = InputExample(guid, words, labels, trigger_word_ids)