code: def get_image_classification_data(composite_flag: bool = True):
      """Method for loading data with images in .npy format (training_data.npy, training_labels.npy,
      test_data.npy, test_labels.npy) that are used in tests.This npy files are a truncated version
      of the MNIST dataset, that contains only 10 first images.
  
      :param composite_flag: Flag that allows to run tests for complex composite models
      """
      test_data_path = "../../data/test_data.npy"
      test_labels_path = "../../data/test_labels.npy"
      train_data_path = "../../data/training_data.npy"
      train_labels_path = "../../data/training_labels.npy"
  
      test_file_path = str(os.path.dirname(__file__))
      training_path_features = os.path.join(
          test_file_path, train_data_path
      )
      training_path_labels = os.path.join(
          test_file_path, train_labels_path
      )
      test_path_features = os.path.join(test_file_path, test_data_path)
      test_path_labels = os.path.join(test_file_path, test_labels_path)
  
      (
          roc_auc_on_valid,
          dataset_to_train,
          dataset_to_validate,
      ) = run_image_classification_problem(
          train_dataset=(training_path_features, training_path_labels),
          test_dataset=(test_path_features, test_path_labels),
          composite_flag=composite_flag,
      )
  
      return roc_auc_on_valid, dataset_to_train, dataset_to_validate
  
imports: import os
  import numpy
  from sklearn.datasets import load_iris, make_classification
  from sklearn.metrics import roc_auc_score
  from examples.simple.classification.image_classification_problem import run_image_classification_problem
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.supplementary_data import SupplementaryData
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from test.integration.models.test_model import classification_dataset_with_redundant_features
label_desc: Use image node_id 6 for calling a global function with example usage: get_image_classification_data(composite_flag) and returns: roc_auc_on_valid,  dataset_to_train,  dataset_to_validate