code: def normalize_values(values: Sized) -> List[float]:
      values = np.array(values, dtype=float)
      vmin, vmax = values.min(), values.max()
      if len(values) > 1:
          values = (values - vmin) / (vmax - vmin)
      return values.tolist()
  
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 a global function with example usage: normalize_values(values) and returns: values