class_docstr: Kaggle Toxic Comment Classification Challenge corpus
  
  You need to download corpus from https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/overview
  to a folder. Then init a JigsawToxicCommentCorpus object with `train.csv` path.
  
  Examples:
  
      >>> from kashgari.corpus import JigsawToxicCommentCorpus
      >>> corpus = JigsawToxicCommentCorpus('<train.csv file-path>')
      >>> train_x, train_y = corpus.load_data('train')
      >>> test_x, test_y = corpus.load_data('test')
      >>> print(train_x)
      [['Please', 'stop', 'being', 'a', 'penis—', 'and', 'Grow', 'Up', 'Regards-'], ...]
      >>> print(train_y)
      [['obscene', 'insult'], ...]
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code: def _text_process(self, text: str) -> List[str]:
      return self.tokenizer.tokenize(text)
  
imports: import os
  from typing import List
  from typing import Tuple
  import numpy
  import pandas
  from tensorflow.keras.utils import get_file
  from kashgari import macros
  from kashgari import utils
  from kashgari.logger import logger
  from kashgari.tokenizers.base_tokenizer import Tokenizer
  from kashgari.tokenizers.bert_tokenizer import BertTokenizer
label_desc: Use image node_id 3 for calling the JigsawToxicCommentCorpus obj's underlying member method code with example usage: obj._text_process(text) and returns: self