class_docstr: Log-transform outcomes.
  
  Useful if the targets are modeled using a (multivariate) log-Normal
  distribution. This means that we can use a standard GP model on the
  log-transformed outcomes and un-transform the model posterior of that GP.
docstr: Un-transform the log-transformed posterior.
  
  Args:
      posterior: A posterior in the log-transformed space.
  
  Returns:
      The un-transformed posterior.
docstr_tok: ["Un-transform","the","log-transformed","posterior",".","Args",":","posterior",":","A","posterior","in","the","log-transformed","space",".","Returns",":","The","un-transformed","posterior","."]
code: def untransform_posterior(
      self, posterior: Posterior
  ) -> TransformedPosterior:
      r"""Un-transform the log-transformed posterior.
  
      Args:
          posterior: A posterior in the log-transformed space.
  
      Returns:
          The un-transformed posterior.
      """
      if self._outputs is not None:
          raise NotImplementedError(
              "Log does not yet support output selection for untransform_posterior"
          )
      return TransformedPosterior(
          posterior=posterior,
          sample_transform=torch.exp,
          mean_transform=norm_to_lognorm_mean,
          variance_transform=norm_to_lognorm_variance,
      )
  
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 Log obj's underlying member method code with example usage: obj.untransform_posterior(posterior) and returns: TransformedPosterior