code: def test_space_tokenization_and_unusual_roberta_tokenization_normalization():
      text = (
          "As a practitioner of ethnic humor from the old days on the Borscht Belt , live "
          "television and the nightclub circuit , Mr. Mason instinctively reached for the "
          "vernacular ."
      )
      space_tokenized = text.split(" ")
      tokenizer = RobertaTokenizer.from_pretrained("roberta-base")
      target_tokenized = tokenizer.tokenize(text)
      # note 1: exposing the target tokenization to highlight an unusual tokenization:
      # " vernacular" -> 'Ġ', 'vern', 'acular' (the usual pattern suggests 'Ġvern', 'acular')
      assert target_tokenized == [
          "As",
          "Ġa",
          "Ġpractitioner",
          "Ġof",
          "Ġethnic",
          "Ġhumor",
          "Ġfrom",
          "Ġthe",
          "Ġold",
          "Ġdays",
          "Ġon",
          "Ġthe",
          "ĠB",
          "ors",
          "cht",
          "ĠBelt",
          "Ġ,",
          "Ġlive",
          "Ġtelevision",
          "Ġand",
          "Ġthe",
          "Ġnightclub",
          "Ġcircuit",
          "Ġ,",
          "ĠMr",
          ".",
          "ĠMason",
          "Ġinstinctively",
          "Ġreached",
          "Ġfor",
          "Ġthe",
          "Ġ",
          "vern",
          "acular",
          "Ġ.",
      ]
      (
          normed_space_tokenized,
          normed_target_tokenized,
      ) = tn.normalize_tokenizations(
          space_tokenized, target_tokenized, tokenizer
      )
      # note: 2: the assert below shows that even with the unusual tokenization (see note 1 above),
      # after normalization the space tokenization and the target tokenization match.
      assert "".join(normed_space_tokenized) == "".join(
          normed_target_tokenized
      )
  
file_path: jiant/tests/utils/test_tokenization_normalization.py
imports: import pytest
  import jiant.utils.tokenization_normalization
  import jiant.utils.tokenization_utils
  from transformers import AlbertTokenizer
  from transformers import BertTokenizer
  from transformers import DebertaV2Tokenizer
  from transformers import RobertaTokenizer
  from transformers import XLMTokenizer
label_desc: Use image node_id 6 for calling a global function with example usage: test_space_tokenization_and_unusual_roberta_tokenization_normalization() without return types