code: def get_multiscale_pipeline(
      window_size1: int = 20, window_size2: int = 100
  ):
      # First branch
      node_lagged_1 = PipelineNode("lagged")
      node_lagged_1.parameters = {"window_size": window_size1}
      node_ridge_1 = PipelineNode("ridge", nodes_from=[node_lagged_1])
  
      # Second branch, which will try to make prediction based on smoothed ts
      node_filtering = PipelineNode("gaussian_filter")
      node_filtering.parameters = {"sigma": 3}
      node_lagged_2 = PipelineNode(
          "lagged", nodes_from=[node_filtering]
      )
      node_lagged_2.parameters = {"window_size": window_size2}
      node_ridge_2 = PipelineNode("ridge", nodes_from=[node_lagged_2])
  
      node_final = PipelineNode(
          "linear", nodes_from=[node_ridge_1, node_ridge_2]
      )
  
      pipeline = Pipeline(node_final)
  
      return pipeline
  
imports: from copy import deepcopy
  from typing import Optional
  import numpy
  import pandas
  import pytest
  from scipy import stats
  from sklearn.metrics import mean_absolute_error, mean_squared_error
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.operations.evaluation.operation_implementations.models.ts_implementations.arima import ARIMAImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.ts_implementations.statsmodels import AutoRegImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.ts_wrappers import in_sample_ts_forecast, out_of_sample_ts_forecast
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import fedot_project_root
  from fedot.utilities.synth_dataset_generator import generate_synthetic_data
label_desc: Use image node_id 4 for calling a global function with example usage: get_multiscale_pipeline(window_size1, window_size2) and returns: pipeline