code: def test_na_scores_on_small_subgroups(adult_split_dataset_and_model):
      # Arrange
      _, test, model = adult_split_dataset_and_model
      check = PerformanceBias("sex", min_subgroup_size=1_000_000_000)
  
      # Act
      result = check.run(test, model)
  
      # Assert
      assert_that(result.value["scores_df"]["_score"].isna().all())
      assert_that(result.value["scores_df"]["_baseline"].isna().all())
  
file_path: deepchecks/tests/tabular/checks/model_evaluation/performance_bias_test.py
imports: import numpy
  import pandas
  from hamcrest import all_of, any_of, assert_that, calling, close_to, equal_to, has_entries, has_items, has_length, has_properties, has_property, raises
  from sklearn.metrics import f1_score, make_scorer
  from deepchecks import ConditionCategory
  from deepchecks.core.errors import DeepchecksNotSupportedError, DeepchecksValueError
  from deepchecks.tabular.checks.model_evaluation import PerformanceBias
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 8 for calling a global function with example usage: test_na_scores_on_small_subgroups(adult_split_dataset_and_model) without return types