class_docstr: Standardize outcomes in a structured multi-output settings by reshaping the
  batched output dimensions to be a vector. Specifically, an output dimension
  of [a x b x c] will be squeezed to be a vector of [a * b * c].
code: def untransform(
      self, Y: Tensor, Yvar: Optional[Tensor] = None
  ) -> Tuple[Tensor, Optional[Tensor]]:
      Y = self._squeeze_to_single_output(Y)
      if Yvar is not None:
          Yvar = self._squeeze_to_single_output(Yvar)
  
      Y, Yvar = super().untransform(Y, Yvar)
  
      Y = self._return_to_output_shape(Y)
      if Yvar is not None:
          Yvar = self._return_to_output_shape(Yvar)
      return Y, Yvar
  
imports: from __future__ import annotations
  import warnings
  from contextlib import ExitStack
  from typing import Any, List, Optional, Tuple, Union
  import torch
  from botorch.acquisition.objective import PosteriorTransform
  from botorch.models.gpytorch import BatchedMultiOutputGPyTorchModel
  from botorch.models.model import FantasizeMixin
  from botorch.models.transforms.input import InputTransform
  from botorch.models.transforms.outcome import OutcomeTransform, Standardize
  from botorch.models.utils import gpt_posterior_settings
  from botorch.models.utils.gpytorch_modules import get_gaussian_likelihood_with_gamma_prior
  from botorch.posteriors import GPyTorchPosterior, HigherOrderGPPosterior, TransformedPosterior
  from gpytorch.distributions import MultivariateNormal
  from gpytorch.kernels import Kernel, MaternKernel
  from gpytorch.likelihoods import Likelihood
  from gpytorch.models import ExactGP
  from gpytorch.priors.torch_priors import GammaPrior, MultivariateNormalPrior
  from gpytorch.settings import fast_pred_var, skip_posterior_variances
  from linear_operator.operators import BatchRepeatLinearOperator, DiagLinearOperator, KroneckerProductLinearOperator, LinearOperator, ZeroLinearOperator
  from linear_operator.settings import _fast_solves
  from torch import Tensor
  from torch.nn import ModuleList, Parameter, ParameterList
label_desc: Use image node_id 5 for calling the FlattenedStandardize obj's underlying member method code with example usage: obj.untransform(Y, Yvar) and returns: Y,  Yvar