class_docstr: A wrapper to make a GPyTorch likelihood compatible with Deep GPs
  
  Example:
      >>> deep_gaussian_likelihood = gpytorch.likelihoods.DeepLikelihood(gpytorch.likelihood.GaussianLikelihood)
class_docstr_tok: ["A","wrapper","to","make","a","GPyTorch","likelihood","compatible","with","Deep","GPs","Example",":",">",">",">","deep_gaussian_likelihood","=","gpytorch.likelihoods.DeepLikelihood","(","gpytorch.likelihood.GaussianLikelihood",")"]
code: def __init__(self, base_likelihood):
      super().__init__()
      warnings.warn(
          "DeepLikelihood is now deprecated. Use a standard likelihood in conjunction with a "
          "gpytorch.mlls.DeepApproximateMLL. See the DeepGP example in our documentation.",
          DeprecationWarning,
      )
      self.base_likelihood = base_likelihood
  
imports: import warnings
  import torch
  from linear_operator.operators import BlockDiagLinearOperator
  from ...None import settings
  from ...distributions import MultitaskMultivariateNormal
  from ...likelihoods import Likelihood
  from ..approximate_gp import ApproximateGP
  from ..gp import GP
label_desc: Use image node_id 1 to create a new DeepLikelihood object from inherited base classes: Likelihood with example: obj = DeepLikelihood(base_likelihood)