code: def test_datasets(self):
      tokenizer, trainer = self.get_tokenizer_trainer()
  
      # In order to keep tests fast, we only use the first 100 examples
      os.environ["TOKENIZERS_PARALLELISM"] = "true"
      dataset = datasets.load_dataset(
          "wikitext", "wikitext-103-raw-v1", split="train[0:100]"
      )
  
      # START def_batch_iterator
      def batch_iterator(batch_size=1000):
          # Only keep the text column to avoid decoding the rest of the columns unnecessarily
          tok_dataset = dataset.select_columns("text")
          for batch in tok_dataset.iter(batch_size):
              yield batch["text"]
  
      # END def_batch_iterator
  
      # START train_datasets
      tokenizer.train_from_iterator(
          batch_iterator(), trainer=trainer, length=len(dataset)
      )
  
file_path: hf-tokenizers/bindings/python/tests/documentation/test_tutorial_train_from_iterators.py
imports: import gzip
  import os
  import datasets
  import pytest
  from ..utils import data_dir, train_files
label_desc: Use image node_id 5 for calling the TestTrainFromIterators obj's underlying member method code with example usage: obj.test_datasets() without return types