class_docstr: Defines an abstract text classification datasets.
  Currently, we only support the following datasets:
  
        - AG_NEWS
        - SogouNews
        - DBpedia
        - YelpReviewPolarity
        - YelpReviewFull
        - YahooAnswers
        - AmazonReviewPolarity
        - AmazonReviewFull
class_docstr_tok: ["Defines","an","abstract","text","classification","datasets",".","Currently",",","we","only","support","the","following","datasets",":","-","AG_NEWS","-","SogouNews","-","DBpedia","-","YelpReviewPolarity","-","YelpReviewFull","-","YahooAnswers","-","AmazonReviewPolarity","-","AmazonReviewFull"]
code: def __iter__(self):
      for x in self._data:
          yield x
  
imports: import csv
  import io
  import logging
  import torch
  from torchtext.data.utils import get_tokenizer, ngrams_iterator
  from torchtext.utils import download_from_url, extract_archive
  from tqdm import tqdm
  from ..vocab import build_vocab_from_iterator, Vocab
label_desc: Use image node_id 4 for calling the TextClassificationDataset obj's underlying member method code with example usage: obj.__iter__() without return types