code: def test_coco_deepchecks_scorer_list_strings_averaging(
      coco_visiondata_train, coco_visiondata_test
  ):
      for avg_method in ["macro", "micro", "weighted"]:
          # Arrange
          scorers = [
              name + "_" + avg_method
              for name in AVAILABLE_EVALUATING_FUNCTIONS.keys()
          ]
          check = ClassPerformance(scorers=scorers)
          # Act
          result = check.run(
              coco_visiondata_train, coco_visiondata_test
          )
          # Assert
          assert_that(result.value, has_length(10))
          assert_that(result.display, has_length(greater_than(0)))
          assert_that(
              set(result.value["Metric"]), equal_to(set(scorers))
          )
  
imports: import re
  import typing
  from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_items, has_length, instance_of, raises
  from plotly.basedatatypes import BaseFigure
  from deepchecks.core.errors import DeepchecksNotSupportedError, DeepchecksValueError
  from deepchecks.vision.checks import ClassPerformance
  from deepchecks.vision.metrics_utils import CustomClassificationScorer
  from deepchecks.vision.metrics_utils.confusion_matrix_counts_metrics import AVAILABLE_EVALUATING_FUNCTIONS
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 13 for calling a global function with example usage: test_coco_deepchecks_scorer_list_strings_averaging(coco_visiondata_train, coco_visiondata_test) without return types