code: def test_image_classification_quality():
      roc_auc_on_valid, _, _ = get_image_classification_data()
      deviation_composite = roc_auc_on_valid - 0.5
  
      roc_auc_on_valid, _, _ = get_image_classification_data(
          composite_flag=False
      )
      deviation_simple = roc_auc_on_valid - 0.5
  
      assert abs(deviation_composite) < 0.25
      assert abs(deviation_simple) < 0.35
  
imports: import numpy
  from test.unit.common_tests import is_predict_ignores_target
  from test.unit.tasks.test_classification import get_image_classification_data
  from fedot.core.operations.evaluation.operation_implementations.models.keras import FedotCNNImplementation, check_input_array, create_deep_cnn, fit_cnn, predict_cnn
label_desc: Use image node_id 3 for calling a global function with example usage: test_image_classification_quality() without return types