code: def test_probabilistic_forecast_accuracy_multivariate(self, config):
      (model_cls, model_kwargs, err), mode = config
      model_kwargs["multi_models"] = mode
      model = model_cls(**model_kwargs)
      if model.supports_multivariate:
          self.helper_test_probabilistic_forecast_accuracy(
              model,
              err,
              self.constant_multivar_ts,
              self.constant_noisy_multivar_ts,
          )
  
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 3 for calling the TestProbabilisticRegressionModels obj's underlying member method code with example usage: obj.test_probabilistic_forecast_accuracy_multivariate(config) without return types