code: def test_models_accuracy_univariate(self, config):
      (model, idx), mode, ocl = config
      # for every model, and different output_chunk_lengths test whether it predicts the univariate time series
      # as well as expected, accuracies are defined at the top of the class
      self.helper_test_models_accuracy(
          self.sine_univariate1,
          self.sine_univariate2,
          self.univariate_accuracies,
          model,
          idx,
          mode,
          ocl,
      )
  
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 10 for calling the TestRegressionModels obj's underlying member method code with example usage: obj.test_models_accuracy_univariate(config) without return types