code: def inverse_transform_proba(self, y, as_pandas=False, as_pred=False):
      if isinstance(y, DataFrame):
          y = copy.deepcopy(y)
          y.columns = copy.deepcopy(self.ordered_class_labels)
          if as_pred:
              y = get_pred_from_proba_df(
                  y, problem_type=self.problem_type_transform
              )
          if not as_pandas:
              y = y.to_numpy()
      elif as_pred:
          y_index = None
          if isinstance(y, Series):
              y_index = y.index
              y = y.to_numpy()
          y = get_pred_from_proba(
              y_pred_proba=y, problem_type=self.problem_type_transform
          )
          y = self._convert_to_valid_series(y)
          y = y.map(self.cat_mappings_dependent_var)
          y = y.to_numpy()
          if as_pandas:
              y = Series(data=y, index=y_index)
      return y
  
imports: import copy
  import logging
  from typing import Union
  import numpy
  from pandas import DataFrame, Series
  from autogluon.core.constants import BINARY, MULTICLASS, QUANTILE, REGRESSION, SOFTCLASS
  from autogluon.core.utils import get_pred_from_proba, get_pred_from_proba_df
label_desc: Use image node_id 2 for calling the LabelCleanerBinary obj's underlying member method code with example usage: obj.inverse_transform_proba(y, as_pandas, as_pred) and returns: y