code: def test_gen(self) -> None:
      self.model_selection_node.fit(
          experiment=self.branin_experiment,
          data=self.branin_experiment.lookup_data(),
      )
      # Check that with `ModelSelectionNode` generation from a node with
      # multiple model specs does not fail.
      gr = self.model_selection_node.gen(
          n=1, pending_observations={"branin": []}
      )
      # Currently, `ModelSelectionNode` should just pick the first model
      # spec as the one to generate from.
      # TODO[adamobeng]: Test correct behavior here when implemented.
      self.assertEqual(gr._model_key, "GPEI")
  
      # test model_to_gen_from_name property
      self.assertEqual(
          self.model_selection_node.model_to_gen_from_name, "GPEI"
      )
  
imports: import logging
  from logging import Logger
  from unittest.mock import patch, PropertyMock
  from ax.core.base_trial import TrialStatus
  from ax.core.observation import ObservationFeatures
  from ax.exceptions.core import UserInputError
  from ax.modelbridge.cross_validation import DiagnosticCriterion, MetricAggregation, SingleDiagnosticBestModelSelector
  from ax.modelbridge.factory import get_sobol
  from ax.modelbridge.generation_node import GenerationNode, GenerationStep
  from ax.modelbridge.model_spec import FactoryFunctionModelSpec, ModelSpec
  from ax.modelbridge.registry import Models
  from ax.modelbridge.transition_criterion import MaxTrials
  from ax.utils.common.logger import get_logger
  from ax.utils.common.testutils import TestCase
  from ax.utils.testing.core_stubs import get_branin_experiment
  from ax.utils.testing.mock import fast_botorch_optimize
label_desc: Use image node_id 2 for calling the TestGenerationNodeWithBestModelSelector obj's underlying member method code with example usage: obj.test_gen() without return types