code: def test_data_splitting_perform_correctly_after_build():
      """
      Check if data splitting perform correctly through Objective Builder - Objective Evaluate
      Case: in-sample validation during cross validation for time series forecasting
      """
      output_by_fold = {
          0: {
              "train_features_size": (12,),
              "test_features_size": (16,),
              "test_target_size": (16,),
          },
          1: {
              "train_features_size": (16,),
              "test_features_size": (20,),
              "test_target_size": (20,),
          },
      }
  
      time_series = get_ts_data_to_forecast_two_elements()
      data_source = DataSourceSplitter(
          cv_folds=2, validation_blocks=2
      ).build(time_series)
  
      # Imitate evaluation process
      for fold_id, (train_data, test_data) in enumerate(data_source()):
          expected_output = output_by_fold[fold_id]
          assert (
              train_data.features.shape
              == expected_output["train_features_size"]
          )
          assert (
              test_data.features.shape
              == expected_output["test_features_size"]
          )
          assert (
              test_data.target.shape
              == expected_output["test_target_size"]
          )
  
imports: from functools import partial
  from typing import Callable
  import numpy
  import pandas
  import pytest
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.optimisers.objective.data_source_splitter import DataSourceSplitter
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import split_data
  from fedot.core.data.cv_folds import cv_generator
  from test.unit.pipelines.test_decompose_pipelines import get_classification_data
  from test.unit.tasks.test_forecasting import get_ts_data
label_desc: Use image node_id 14 for calling a global function with example usage: test_data_splitting_perform_correctly_after_build() without return types