code: def test_run_tweet_emotion(
      tweet_emotion_train_test_textdata,
      tweet_emotion_train_test_predictions,
  ):
      # Arrange
      check = ConfusionMatrixReport()
  
      # Act
      result = check.run(
          tweet_emotion_train_test_textdata[0],
          predictions=tweet_emotion_train_test_predictions[0],
      )
  
      confusion_matrix = result.value.to_numpy()
  
      # Assert
      assert_that(confusion_matrix[0][0], close_to(1160, 0.001))
      assert_that(confusion_matrix.shape[0], close_to(4, 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 4 for calling a global function with example usage: test_run_tweet_emotion(tweet_emotion_train_test_textdata, tweet_emotion_train_test_predictions) without return types