code: def test_confusion_matrix_report_display(mnist_visiondata_train):
      # Arrange
      check = ConfusionMatrixReport()
  
      # Act
      result = check.run(mnist_visiondata_train)
  
      # Assert
      assert_that(
          result.display[0], equal_to("Showing 10 of 10 classes:")
      )
      assert_that(
          result.display[1],
          equal_to(
              "The overall accuracy of your model is: 97.45%.<br>Best accuracy achieved on samples with <b>"
              "0</b> label (100.0%).<br>Worst accuracy achieved on samples with <b>9</b> label (86.96%)."
          ),
      )
      # First and second are the text descriptions and third is a heatmap
      assert_that(len(result.display), equal_to(3))
      assert_that(len(result.display[2].data), equal_to(1))
      assert_that(result.display[2].data[0].type, equal_to("heatmap"))
  
file_path: deepchecks/tests/vision/checks/model_evaluation/confusion_matrix_test.py
imports: from hamcrest import assert_that, equal_to, greater_than, has_length
  from hamcrest import less_than_or_equal_to
  from deepchecks.vision.checks import ConfusionMatrixReport
label_desc: Use image node_id 5 for calling a global function with example usage: test_confusion_matrix_report_display(mnist_visiondata_train) without return types