class_docstr: A single-task exact GP model using fixed noise levels.
  
  DEPRECATED: `FixedNoiseGP` has been merged into `SingleTaskGP`. Please use
  `SingleTaskGP` with `train_Yvar` instead.
  Will be removed in a future release (~v0.12).
docstr: DEPRECATED. See SingleTaskGP.
code: def __init__(
      self,
      train_X: Tensor,
      train_Y: Tensor,
      train_Yvar: Tensor,
      covar_module: Optional[Module] = None,
      mean_module: Optional[Mean] = None,
      outcome_transform: Optional[OutcomeTransform] = None,
      input_transform: Optional[InputTransform] = None,
  ) -> None:
      r"""DEPRECATED. See SingleTaskGP."""
      warnings.warn(
          "`FixedNoiseGP` has been merged into `SingleTaskGP`. "
          "Please use `SingleTaskGP` with `train_Yvar` instead.",
          DeprecationWarning,
      )
      super().__init__(
          train_X=train_X,
          train_Y=train_Y,
          train_Yvar=train_Yvar,
          covar_module=covar_module,
          mean_module=mean_module,
          outcome_transform=outcome_transform,
          input_transform=input_transform,
      )
  
imports: from __future__ import annotations
  import warnings
  from typing import NoReturn, Optional
  import torch
  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 Log, OutcomeTransform
  from botorch.models.utils import validate_input_scaling
  from botorch.models.utils.gpytorch_modules import get_gaussian_likelihood_with_gamma_prior, get_matern_kernel_with_gamma_prior, MIN_INFERRED_NOISE_LEVEL
  from gpytorch.constraints.constraints import GreaterThan
  from gpytorch.distributions.multivariate_normal import MultivariateNormal
  from gpytorch.likelihoods.gaussian_likelihood import _GaussianLikelihoodBase, FixedNoiseGaussianLikelihood, GaussianLikelihood
  from gpytorch.likelihoods.likelihood import Likelihood
  from gpytorch.likelihoods.noise_models import HeteroskedasticNoise
  from gpytorch.means.constant_mean import ConstantMean
  from gpytorch.means.mean import Mean
  from gpytorch.mlls.noise_model_added_loss_term import NoiseModelAddedLossTerm
  from gpytorch.models.exact_gp import ExactGP
  from gpytorch.module import Module
  from gpytorch.priors.smoothed_box_prior import SmoothedBoxPrior
  from torch import Tensor
label_desc: Use image node_id 1 to create a new FixedNoiseGP object from inherited base classes: SingleTaskGP with example: obj = FixedNoiseGP(train_X, train_Y, train_Yvar, covar_module, mean_module, outcome_transform, input_transform)