code: def test_choose_model_class_task_features(self) -> None:
      # Only a single task feature can be used.
      with self.assertRaisesRegex(
          NotImplementedError, "Only a single task feature"
      ):
          choose_model_class(
              datasets=self.fixed_noise_datasets,
              search_space_digest=SearchSpaceDigest(
                  feature_names=[], bounds=[], task_features=[1, 2]
              ),
          )
      # With task features use MultiTaskGP.
      for datasets in (
          self.supervised_datasets,
          self.fixed_noise_datasets,
      ):
          self.assertEqual(
              MultiTaskGP,
              choose_model_class(
                  datasets=datasets,
                  search_space_digest=SearchSpaceDigest(
                      feature_names=[], bounds=[], task_features=[1]
                  ),
              ),
          )
  
imports: import warnings
  from typing import OrderedDict
  import numpy
  import torch
  from ax.core.search_space import SearchSpaceDigest
  from ax.exceptions.core import AxError, AxWarning, UnsupportedError
  from ax.models.torch.botorch_modular.utils import _get_shared_rows, _tensor_difference, check_metric_dataset_match, choose_botorch_acqf_class, choose_model_class, construct_acquisition_and_optimizer_options, convert_to_block_design, get_subset_datasets, subset_state_dict, use_model_list
  from ax.models.torch.utils import _to_inequality_constraints
  from ax.utils.common.constants import Keys
  from ax.utils.common.testutils import TestCase
  from ax.utils.common.typeutils import checked_cast, not_none
  from ax.utils.testing.torch_stubs import get_torch_test_data
  from botorch.acquisition import qLogNoisyExpectedImprovement
  from botorch.acquisition.multi_objective.logei import qLogNoisyExpectedHypervolumeImprovement
  from botorch.models.fully_bayesian import SaasFullyBayesianSingleTaskGP
  from botorch.models.gp_regression import SingleTaskGP
  from botorch.models.gp_regression_fidelity import SingleTaskMultiFidelityGP
  from botorch.models.gp_regression_mixed import MixedSingleTaskGP
  from botorch.models.model_list_gp_regression import ModelListGP
  from botorch.models.multitask import MultiTaskGP
  from botorch.utils.datasets import SupervisedDataset
label_desc: Use image node_id 3 for calling the BoTorchModelUtilsTest obj's underlying member method code with example usage: obj.test_choose_model_class_task_features() without return types