class_docstr: Bilog-transform outcomes.
  
  The Bilog transform [eriksson2021scalable]_ is useful for modeling outcome
  constraints as it magnifies values near zero and flattens extreme values.
docstr: Un-transform the bilog-transformed posterior.
  
  Args:
      posterior: A posterior in the bilog-transformed space.
  
  Returns:
      The un-transformed posterior.
docstr_tok: ["Un-transform","the","bilog-transformed","posterior",".","Args",":","posterior",":","A","posterior","in","the","bilog-transformed","space",".","Returns",":","The","un-transformed","posterior","."]
code: def untransform_posterior(
      self, posterior: Posterior
  ) -> TransformedPosterior:
      r"""Un-transform the bilog-transformed posterior.
  
      Args:
          posterior: A posterior in the bilog-transformed space.
  
      Returns:
          The un-transformed posterior.
      """
      if self._outputs is not None:
          raise NotImplementedError(
              "Bilog does not yet support output selection for untransform_posterior"
          )
      return TransformedPosterior(
          posterior=posterior,
          sample_transform=lambda x: x.sign() * (x.abs().exp() - 1.0),
      )
  
imports: from __future__ import annotations
  import warnings
  from abc import ABC, abstractmethod
  from collections import OrderedDict
  from typing import Any, List, Mapping, Optional, Tuple, Union
  import torch
  from botorch.models.transforms.utils import norm_to_lognorm_mean, norm_to_lognorm_variance
  from botorch.posteriors import GPyTorchPosterior, Posterior, TransformedPosterior
  from botorch.utils.transforms import normalize_indices
  from linear_operator.operators import CholLinearOperator, DiagLinearOperator
  from torch import Tensor
  from torch.nn import Module, ModuleDict
label_desc: Use image node_id 5 for calling the Bilog obj's underlying member method code with example usage: obj.untransform_posterior(posterior) and returns: TransformedPosterior