code: def get_scoring_data() -> Tuple[InputData, InputData]:
      train_data_path = (
          f"{fedot_project_root()}/cases/data/scoring/scoring_train.csv"
      )
      test_data_path = (
          f"{fedot_project_root()}/cases/data/scoring/scoring_test.csv"
      )
  
      train_data = InputData.from_csv(train_data_path)
      test_data = InputData.from_csv(test_data_path)
  
      return train_data, test_data
  
file_path: FEDOT/examples/advanced/gpu_example.py
imports: from datetime import datetime
  from typing import Tuple
  from sklearn.datasets import make_moons
  from examples.simple.classification.classification_pipelines import classification_svc_complex_pipeline
  from fedot import Fedot
  from fedot.core.data.data import InputData
  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 fedot.core.utils import fedot_project_root
label_desc: Use image node_id 3 for calling a global function with example usage: get_scoring_data() and returns: train_data,  test_data