code: def yield_tokens(data_iter, ngrams):
      for _, text in data_iter:
          yield ngrams_iterator(tokenizer(text), ngrams)
  
file_path: serve/examples/text_classification/train.py
imports: import os
  import logging
  import argparse
  import time
  from typing import Text
  import torch
  import sys
  from torchtext.utils import download_from_url
  from model import TextSentiment
  from torch.utils.data import DataLoader
  from torch.utils.data.dataset import random_split
  from torchtext.data.functional import to_map_style_dataset
  from torchtext.datasets import DATASETS
  from torchtext.data.utils import get_tokenizer, ngrams_iterator
  from torchtext.vocab import build_vocab_from_iterator
label_desc: Use image node_id 2 for calling a global function with example usage: yield_tokens(data_iter, ngrams) without return types