code: def AG_NEWS(*args, **kwargs):
      """Defines AG_NEWS datasets.
  
      The labels include:
  
          - 0 : World
          - 1 : Sports
          - 2 : Business
          - 3 : Sci/Tech
  
      Create supervised learning dataset: AG_NEWS
  
      Separately returns the training and test dataset
  
      Args:
          root: Directory where the datasets are saved. Default: ".data"
          ngrams: a contiguous sequence of n items from s string text.
              Default: 1
          vocab: Vocabulary used for dataset. If None, it will generate a new
              vocabulary based on the train data set.
          include_unk: include unknown token in the data (Default: False)
  
      Examples:
          >>> train_dataset, test_dataset = torchtext.datasets.AG_NEWS(ngrams=3)
  
      """
  
      return _setup_datasets(*(("AG_NEWS",) + args), **kwargs)
  
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 a global function with example usage: AG_NEWS() and returns: _setup_datasets