code: def test_group_singleton_words_true(
      dataset_with_reoccurring_unknown_words,
  ):
      # Arrange
      check = UnknownTokens(
          group_singleton_words=True
      ).add_condition_ratio_of_unknown_words_less_or_equal()
  
      # Act
      result = check.run(dataset=dataset_with_reoccurring_unknown_words)
      conditions_decisions = check.conditions_decision(result)
  
      # Assert
      assert_that(
          result.value,
          has_entries(
              {
                  "unknown_word_ratio": close_to(0.1111, 0.0001),
                  "unknown_word_details": instance_of(dict),
              }
          ),
      )
  
      assert_that(
          conditions_decisions[0],
          equal_condition_result(
              is_pass=False,
              details=f'Ratio was {format_percent(result.value["unknown_word_ratio"])}',
              name="Ratio of unknown words is less than 0%",
          ),
      )  # type: ignore
  
      # Check if the display has a 'Other Unknown Words' label
      display = result.display
      assert_that(display, has_length(2))
      pie_chart = display[0]
      assert_that(
          pie_chart["data"][0]["labels"],
          has_item("Other Unknown Words"),
      )
  
file_path: deepchecks/tests/nlp/checks/data_integrity/unknown_tokens_test.py
imports: import pytest
  from hamcrest import *
  from transformers import AutoTokenizer, BertTokenizer
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.nlp.checks import UnknownTokens
  from deepchecks.nlp.text_data import TextData
  from deepchecks.utils.strings import format_percent
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 7 for calling a global function with example usage: test_group_singleton_words_true(dataset_with_reoccurring_unknown_words) without return types