code: def test_batch_encoding_is_fast(self):
      tokenizer_p = BertTokenizer.from_pretrained("bert-base-cased")
      tokenizer_r = BertTokenizerFast.from_pretrained("bert-base-cased")
  
      with self.subTest("Python Tokenizer"):
          self.assertFalse(
              tokenizer_p("Small example to_encode").is_fast
          )
  
      with self.subTest("Rust Tokenizer"):
          self.assertTrue(
              tokenizer_r("Small example to_encode").is_fast
          )
  
imports: import os
  import pickle
  import tempfile
  import unittest
  from typing import Callable, Optional
  import numpy
  from transformers import PreTrainedTokenizerFast
  from transformers import BatchEncoding, BertTokenizer, BertTokenizerFast, PreTrainedTokenizer, TensorType, TokenSpan, is_tokenizers_available
  from transformers.models.gpt2.tokenization_gpt2 import GPT2Tokenizer
  from transformers.testing_utils import CaptureStderr, require_flax, require_tf, require_tokenizers, require_torch, slow
label_desc: Use image node_id 8 for calling the TokenizerUtilsTest obj's underlying member method code with example usage: obj.test_batch_encoding_is_fast() without return types