code: def test_pipeline_objective_evaluate_for_timeseries_cv(
      folds, actual_value
  ):
      (
          forecast_len,
          validation_blocks,
          time_series,
      ) = configure_experiment()
      objective = MetricsObjective(RegressionMetricsEnum.MSE)
      data_producer = DataSourceSplitter(
          folds, validation_blocks
      ).build(time_series)
      simple_pipeline = get_simple_ts_pipeline()
      objective_evaluate = PipelineObjectiveEvaluate(
          objective, data_producer, validation_blocks=validation_blocks
      )
      metric_value = objective_evaluate.evaluate(simple_pipeline).value
      assert np.isclose(metric_value, actual_value)
  
imports: import datetime
  from copy import deepcopy
  import numpy
  import pytest
  from golem.core.optimisers.fitness import SingleObjFitness
  from fedot.core.data.data import InputData
  from fedot.core.data.supplementary_data import SupplementaryData
  from fedot.core.optimisers.objective import PipelineObjectiveEvaluate
  from fedot.core.optimisers.objective.data_source_splitter import DataSourceSplitter
  from fedot.core.optimisers.objective.metrics_objective import MetricsObjective
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.pipeline_builder import PipelineBuilder
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.metrics_repository import ClassificationMetricsEnum, MetricsRepository, RegressionMetricsEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from test.integration.models.test_model import classification_dataset, classification_dataset_with_str_labels
  from test.unit.tasks.test_forecasting import get_simple_ts_pipeline
  from test.unit.validation.test_table_cv import sample_pipeline
  from test.unit.validation.test_time_series_cv import configure_experiment
label_desc: Use image node_id 15 for calling a global function with example usage: test_pipeline_objective_evaluate_for_timeseries_cv(folds, actual_value) without return types