code: def setUp(self) -> None:
      self.search_space = SearchSpace(
          parameters=[
              RangeParameter(
                  "x",
                  lower=1,
                  upper=3,
                  parameter_type=ParameterType.FLOAT,
              ),
              RangeParameter(
                  "a",
                  lower=1,
                  upper=2,
                  parameter_type=ParameterType.INT,
              ),
              ChoiceParameter(
                  "b",
                  parameter_type=ParameterType.FLOAT,
                  values=[1.0, 10.0, 100.0],
                  is_ordered=True,
              ),
              ChoiceParameter(
                  "c",
                  parameter_type=ParameterType.FLOAT,
                  values=[10.0, 100.0, 1000.0],
                  is_ordered=True,
                  sort_values=False,
              ),
              ChoiceParameter(
                  "d",
                  parameter_type=ParameterType.STRING,
                  values=["r", "q", "z"],
                  sort_values=True,
              ),
              ChoiceParameter(
                  "e",
                  parameter_type=ParameterType.STRING,
                  values=["r", "q", "z"],
                  is_ordered=False,
                  sort_values=False,
              ),
          ],
          parameter_constraints=[
              ParameterConstraint(
                  constraint_dict={"x": -0.5, "a": 1}, bound=0.5
              )
          ],
      )
      self.t = self.t_class(
          search_space=self.search_space,
          observations=[],
      )
      self.observation_features = [
          ObservationFeatures(
              parameters={
                  "x": 2.2,
                  "a": 2,
                  "b": 10.0,
                  "c": 10.0,
                  "d": "r",
              }
          )
      ]
      # expected parameters after transform
      self.expected_transformed_params = {
          "x": 2.2,
          "a": 2,
          # ordered float choice originally; transformed normalized value
          "b": normalize_values([1.0, 10.0, 100.0])[1],
          # ordered float choice originally; transformed normalized value
          "c": normalize_values([10.0, 100.0, 1000.0])[0],
          # string choice originally; transformed to int index.
          "d": 1,
      }
  
imports: from copy import deepcopy
  from typing import List, Sized
  import numpy
  from ax.core.observation import ObservationFeatures
  from ax.core.parameter import ChoiceParameter, ParameterType, RangeParameter
  from ax.core.parameter_constraint import ParameterConstraint
  from ax.core.search_space import RobustSearchSpace, SearchSpace
  from ax.modelbridge.transforms.choice_encode import ChoiceEncode, OrderedChoiceEncode
  from ax.utils.common.testutils import TestCase
  from ax.utils.common.typeutils import checked_cast
  from ax.utils.testing.core_stubs import get_robust_search_space
label_desc: Use image node_id 1 for calling the ChoiceEncodeTransformTest obj's underlying member method code with example usage: obj.setUp() without return types