code: def __init__(self, *args, **kwargs):
      # Remove after 1.0
      warnings.warn(
          "VariationalELBOEmpirical is deprecated. Please use VariationalELBO instead.",
          DeprecationWarning,
      )
      super().__init__(*args, **kwargs)
  
file_path: gpytorch/gpytorch/mlls/__init__.py
imports: import warnings
  from .added_loss_term import AddedLossTerm
  from .deep_approximate_mll import DeepApproximateMLL
  from .deep_predictive_log_likelihood import DeepPredictiveLogLikelihood
  from .exact_marginal_log_likelihood import ExactMarginalLogLikelihood
  from .gamma_robust_variational_elbo import GammaRobustVariationalELBO
  from .inducing_point_kernel_added_loss_term import InducingPointKernelAddedLossTerm
  from .kl_gaussian_added_loss_term import KLGaussianAddedLossTerm
  from .leave_one_out_pseudo_likelihood import LeaveOneOutPseudoLikelihood
  from .marginal_log_likelihood import MarginalLogLikelihood
  from .noise_model_added_loss_term import NoiseModelAddedLossTerm
  from .predictive_log_likelihood import PredictiveLogLikelihood
  from .sum_marginal_log_likelihood import SumMarginalLogLikelihood
  from .variational_elbo import VariationalELBO
label_desc: Use image node_id 1 to create a new VariationalELBOEmpirical object from inherited base classes: VariationalELBO with example: obj = VariationalELBOEmpirical()