class_docstr: Posterior transform that unstandardizes the posterior.
  
  TODO: remove this when MultiTask models support outcome transforms.
  
  Example:
      >>> unstd_transform = UnstandardizePosteriorTransform(Y_mean, Y_std)
      >>> unstd_posterior = unstd_transform(posterior)
class_docstr_tok: ["Posterior","transform","that","unstandardizes","the","posterior",".","TODO",":","remove","this","when","MultiTask","models","support","outcome","transforms",".","Example",":",">",">",">","unstd_transform","=","UnstandardizePosteriorTransform","(","Y_mean",",","Y_std",")",">",">",">","unstd_posterior","=","unstd_transform","(","posterior",")"]
code: def evaluate(self, Y: Tensor) -> Tensor:
      return self.outcome_transform.untransform(Y)[0]
  
imports: from __future__ import annotations
  import inspect
  import warnings
  from abc import ABC, abstractmethod
  from typing import Callable, List, Optional, TYPE_CHECKING, Union
  import torch
  from botorch.exceptions.errors import BotorchTensorDimensionError, UnsupportedError
  from botorch.exceptions.warnings import InputDataWarning
  from botorch.models.model import Model
  from botorch.models.transforms.outcome import Standardize
  from botorch.posteriors.gpytorch import GPyTorchPosterior, scalarize_posterior
  from botorch.sampling import IIDNormalSampler
  from botorch.utils import apply_constraints
  from gpytorch.distributions import MultitaskMultivariateNormal, MultivariateNormal
  from linear_operator.operators.dense_linear_operator import to_linear_operator
  from torch import Tensor
  from torch.nn import Module
  from botorch.models.deterministic import DeterministicModel
label_desc: Use image node_id 2 for calling the UnstandardizePosteriorTransform obj's underlying member method code with example usage: obj.evaluate(Y) and returns: self