class_docstr: This is the Sparse Variational GP (SVGP).
  
  The key reference is :cite:t:`hensman2014scalable`.
  
  For a use example see
  :doc:`../../../../notebooks/getting_started/classification_and_other_data_distributions`.
class_docstr_tok: ["This","is","the","Sparse","Variational","GP","(","SVGP",")",".","The","key","reference","is",":","cite",":","t",":","`","hensman2014scalable","`",".","For","a","use","example","see",":","doc",":","`","..","\/","..","\/","..","\/","..","\/notebooks\/getting_started\/classification_and_other_data_distributions","`","."]
code: def maximum_log_likelihood_objective(self, data: RegressionData) -> tf.Tensor:  # type: ignore[override]
      return self.elbo(data)
  
imports: from typing import Optional
  import numpy
  import tensorflow
  from check_shapes import check_shapes, inherit_check_shapes
  from ..None import kullback_leiblers, posteriors
  from ..base import AnyNDArray, InputData, MeanAndVariance, Parameter, RegressionData
  from ..conditionals import conditional
  from ..config import default_float
  from ..inducing_variables import InducingVariables
  from ..kernels import Kernel
  from ..likelihoods import Likelihood
  from ..mean_functions import MeanFunction
  from ..utilities import positive, triangular
  from .model import GPModel
  from .training_mixins import ExternalDataTrainingLossMixin
  from .util import InducingVariablesLike, inducingpoint_wrapper
label_desc: Use image node_id 4 for calling the SVGP_deprecated obj's underlying member method code with example usage: obj.maximum_log_likelihood_objective(data) and returns: self