class_docstr: Joins the two encoders needed for OneHot transform.
docstr: Inverse transorm a list of one hot encoded labels.
docstr_tok: ["Inverse","transorm","a","list","of","one","hot","encoded","labels","."]
code: def inverse_transform(self, encoded_labels: List[T]) -> List[T]:
      """Inverse transorm a list of one hot encoded labels."""
      return self.int_encoder.inverse_transform(
          self.label_binarizer.inverse_transform(encoded_labels)
      )
  
imports: from typing import Dict, List, Optional, TYPE_CHECKING, TypeVar
  import numpy
  from ax.core.observation import Observation, ObservationFeatures
  from ax.core.parameter import ChoiceParameter, Parameter, ParameterType, RangeParameter
  from ax.core.search_space import SearchSpace
  from ax.core.types import TParameterization
  from ax.modelbridge.transforms.base import Transform
  from ax.modelbridge.transforms.rounding import randomized_onehot_round, strict_onehot_round
  from ax.modelbridge.transforms.utils import construct_new_search_space
  from ax.models.types import TConfig
  from sklearn.preprocessing import LabelBinarizer, LabelEncoder
label_desc: Use image node_id 3 for calling the OneHotEncoder obj's underlying member method code with example usage: obj.inverse_transform(encoded_labels) and returns: self