code: def helper_create_LinearModel(
      self, multi_models=True, extreme_lags=False
  ):
      if not extreme_lags:
          lags, lags_pc, lags_fc = 3, 3, [-3, -2, -1, 0]
      else:
          lags, lags_pc, lags_fc = None, [-3], [1]
      return LinearRegressionModel(
          lags=lags,
          lags_past_covariates=lags_pc,
          lags_future_covariates=lags_fc,
          output_chunk_length=1,
          multi_models=multi_models,
          add_encoders={
              "datetime_attribute": {
                  "past": ["month", "dayofweek"],
                  "future": ["month", "dayofweek"],
              }
          },
      )
  
imports: import copy
  import functools
  import itertools
  import math
  from unittest.mock import patch
  import numpy
  import pandas
  import pytest
  from sklearn.ensemble import HistGradientBoostingRegressor, RandomForestRegressor
  from sklearn.linear_model import LinearRegression
  import darts
  from darts import TimeSeries
  from darts.dataprocessing.encoders import FutureCyclicEncoder, PastDatetimeAttributeEncoder
  from darts.logging import get_logger
  from darts.metrics import mae, rmse
  from darts.models import CatBoostModel, LightGBMModel, LinearRegressionModel, NotImportedModule, RandomForest, RegressionModel, XGBModel
  from darts.utils import timeseries_generation
  from darts.utils.multioutput import MultiOutputRegressor
label_desc: Use image node_id 35 for calling the TestRegressionModels obj's underlying member method code with example usage: obj.helper_create_LinearModel(multi_models, extreme_lags) and returns: LinearRegressionModel