code: def test_gen(self, mock_init: Mock) -> None:
      # Test with constraints
      optimization_config = OptimizationConfig(
          objective=Objective(Metric("a"), minimize=True),
          outcome_constraints=[
              OutcomeConstraint(Metric("b"), ComparisonOp.GEQ, 2, False)
          ],
      )
      # pyre-fixme[20]: Argument `model` expected.
      ma = DiscreteModelBridge()
      # Test validation.
      with self.assertRaisesRegex(
          UserInputError, "positive integer or -1."
      ):
          ma._validate_gen_inputs(n=0)
      ma._validate_gen_inputs(n=-1)
      # Test rest of gen.
      model = mock.MagicMock(
          DiscreteModel, autospec=True, instance=True
      )
      model.gen.return_value = (
          [[0.0, 2.0, 3.0], [1.0, 1.0, 3.0]],
          [1.0, 2.0],
          {},
      )
      ma.model = model
      ma.parameters = ["x", "y", "z"]
      ma.outcomes = ["a", "b"]
      gen_results = ma._gen(
          n=3,
          search_space=self.search_space,
          optimization_config=optimization_config,
          pending_observations=self.pending_observations,
          fixed_features=ObservationFeatures({}),
          # pyre-fixme[6]: For 6th param expected `Optional[Dict[str, Union[None,
          #  Dict[str, typing.Any], OptimizationConfig, AcquisitionFunction, float,
          #  int, str]]]` but got `Dict[str, str]`.
          model_gen_options=self.model_gen_options,
      )
      gen_args = model.gen.mock_calls[0][2]
      self.assertEqual(gen_args["n"], 3)
      self.assertEqual(
          gen_args["parameter_values"],
          [[0.0, 1.0], ["foo", "bar"], [True]],
      )
      self.assertTrue(
          np.array_equal(
              gen_args["objective_weights"], np.array([-1.0, 0.0])
          )
      )
      self.assertTrue(
          np.array_equal(
              gen_args["outcome_constraints"][0],
              np.array([[0.0, -1.0]]),
          )
      )
      self.assertTrue(
          np.array_equal(
              gen_args["outcome_constraints"][1], np.array([[-2]])
          )
      )
      self.assertEqual(gen_args["pending_observations"][0], [])
      self.assertEqual(
          gen_args["pending_observations"][1], [[0, "foo", True]]
      )
      self.assertEqual(gen_args["model_gen_options"], {"option": "yes"})
      self.assertEqual(
          gen_results.observation_features[0].parameters,
          {"x": 0.0, "y": 2.0, "z": 3.0},
      )
      self.assertEqual(
          gen_results.observation_features[1].parameters,
          {"x": 1.0, "y": 1.0, "z": 3.0},
      )
      self.assertEqual(gen_results.weights, [1.0, 2.0])
  
      # Test with no constraints, no fixed feature, no pending observations
      # pyre-fixme[6]: For 1st param expected `List[Parameter]` but got
      #  `List[Union[ChoiceParameter, FixedParameter]]`.
      search_space = SearchSpace(self.parameters[:2])
      optimization_config.outcome_constraints = []
      ma.parameters = ["x", "y"]
      ma._gen(
          n=3,
          search_space=search_space,
          optimization_config=optimization_config,
          pending_observations={},
          fixed_features=ObservationFeatures({}),
          model_gen_options={},
      )
      gen_args = model.gen.mock_calls[1][2]
      self.assertEqual(
          gen_args["parameter_values"], [[0.0, 1.0], ["foo", "bar"]]
      )
      self.assertIsNone(gen_args["outcome_constraints"])
      self.assertIsNone(gen_args["pending_observations"])
  
      # Test validation
      optimization_config = OptimizationConfig(
          objective=Objective(Metric("a"), minimize=False),
          outcome_constraints=[
              OutcomeConstraint(Metric("b"), ComparisonOp.GEQ, 2, True)
          ],
      )
      with self.assertRaises(ValueError):
          ma._gen(
              n=3,
              search_space=search_space,
              optimization_config=optimization_config,
              pending_observations={},
              fixed_features=ObservationFeatures({}),
              model_gen_options={},
          )
  
imports: from unittest import mock
  from unittest.mock import Mock
  import numpy
  from ax.core.metric import Metric
  from ax.core.objective import Objective
  from ax.core.observation import Observation, ObservationData, ObservationFeatures
  from ax.core.optimization_config import OptimizationConfig
  from ax.core.outcome_constraint import ComparisonOp, OutcomeConstraint
  from ax.core.parameter import ChoiceParameter, FixedParameter, ParameterType, RangeParameter
  from ax.core.search_space import SearchSpace
  from ax.exceptions.core import UserInputError
  from ax.modelbridge.discrete import _get_parameter_values, DiscreteModelBridge
  from ax.models.discrete_base import DiscreteModel
  from ax.utils.common.testutils import TestCase
label_desc: Use image node_id 4 for calling the DiscreteModelBridgeTest obj's underlying member method code with example usage: obj.test_gen(mock_init) without return types