code: def get_split_data_paths(directory_names: list):
      train_file_path = os.path.join(
          directory_names[0],
          directory_names[1],
          directory_names[2],
          "train.csv",
      )
      full_train_file_path = os.path.join(
          str(fedot_project_root()), train_file_path
      )
      test_file_path = os.path.join(
          directory_names[0],
          directory_names[1],
          directory_names[2],
          "test.csv",
      )
      full_test_file_path = os.path.join(
          str(fedot_project_root()), test_file_path
      )
      return full_train_file_path, full_test_file_path
  
imports: import math
  import os
  import platform
  import random
  import tempfile
  from pathlib import Path
  from typing import Optional, Union
  import numpy
  import pandas
  from golem.utilities.random import RandomStateHandler
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 7 for calling a global function with example usage: get_split_data_paths(directory_names) and returns: full_train_file_path,  full_test_file_path