code: def get_multi_ts_data(
      forecast_length: int = 5, validation_blocks: Optional[int] = None
  ):
      task = Task(
          TaskTypesEnum.ts_forecasting,
          TsForecastingParams(forecast_length=forecast_length),
      )
      file_path = fedot_project_root().joinpath(
          "test/data/synthetic_multi_ts.csv"
      )
      data = InputData.from_csv_multi_time_series(
          file_path=file_path, task=task
      )
      train_data, test_data = train_test_data_setup(
          data, validation_blocks=validation_blocks
      )
      return train_data, test_data
  
file_path: FEDOT/test/unit/tasks/test_multi_ts_forecast.py
imports: from typing import Optional
  import numpy
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import fedot_project_root
label_desc: Use image node_id 1 for calling a global function with example usage: get_multi_ts_data(forecast_length, validation_blocks) and returns: train_data,  test_data