code: def get_binary_classification_data():
      test_file_path = str(os.path.dirname(__file__))
      file = "../../data/simple_classification.csv"
      input_data = InputData.from_csv(
          os.path.join(test_file_path, file)
      )
      return input_data
  
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 5 for calling a global function with example usage: get_binary_classification_data() and returns: input_data