code: def test_run_default_scorer_string_class(
      text_classification_string_class_dataset_mock,
  ):
      # Arrange
      check = ConfusionMatrixReport()
  
      # Act
      result = check.run(
          text_classification_string_class_dataset_mock,
          predictions=["wise", "wise", "meh"],
      )
  
      confusion_matrix = result.value.to_numpy()
  
      # Assert
      assert_that(
          list(text_classification_string_class_dataset_mock.label),
          equal_to(["wise", "meh", "meh"]),
      )
      assert_that(confusion_matrix[0][0], close_to(1, 0.001))
      assert_that(confusion_matrix.shape[0], close_to(2, 0.001))
  
file_path: deepchecks/tests/nlp/checks/model_evaluation/confusion_matrix_test.py
imports: import numpy
  from hamcrest import assert_that, close_to, equal_to
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.nlp.checks.model_evaluation import ConfusionMatrixReport
  from deepchecks.utils.strings import format_number, format_percent
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 2 for calling a global function with example usage: test_run_default_scorer_string_class(text_classification_string_class_dataset_mock) without return types