class_docstr: Conjugate Gradient Lower Bound.
  
  The key reference is :cite:t:`pmlr-v139-artemev21a`.
  
  :param cg_tolerance: Determines accuracy to which conjugate
      gradient is run when evaluating the elbo. Running more
      iterations of CG would increase the ELBO by at most
      `cg_tolerance`.
  
  :param max_cg_iters: Maximum number of iterations of CG to run
      per evaluation of the ELBO (or mean prediction).
  
  :param restart_cg_iters: How frequently to restart the CG iteration.
      Can be useful to avoid build up of numerical errors when
      many steps of CG are run.
  
  :param v_grad_optimization: If False, in every evaluation of the
      ELBO, CG is run to select a new auxilary vector `v`. If
      False, no CG is run when evaluating the ELBO but
      gradients with respect to `v` are tracked so that it can
      be optimized jointly with other parameters.
class_docstr_tok: ["Conjugate","Gradient","Lower","Bound",".","The","key","reference","is",":","cite",":","t",":","`","pmlr-v139-artemev21a","`",".",":","param","cg_tolerance",":","Determines","accuracy","to","which","conjugate","gradient","is","run","when","evaluating","the","elbo",".","Running","more","iterations","of","CG","would","increase","the","ELBO","by","at","most","`","cg_tolerance","`",".",":","param","max_cg_iters",":","Maximum","number","of","iterations","of","CG","to","run","per","evaluation","of","the","ELBO","(","or","mean","prediction",")",".",":","param","restart_cg_iters",":","How","frequently","to","restart","the","CG","iteration",".","Can","be","useful","to","avoid","build","up","of","numerical","errors","when","many","steps","of","CG","are","run",".",":","param","v_grad_optimization",":","If","False",",","in","every","evaluation","of","the","ELBO",",","CG","is","run","to","select","a","new","auxilary","vector","`","v","`",".","If","False",",","no","CG","is","run","when","evaluating","the","ELBO","but","gradients","with","respect","to","`","v","`","are","tracked","so","that","it","can","be","optimized","jointly","with","other","parameters","."]
code: def aux_vec(self) -> Parameter:
      return self._v
  
imports: from typing import Any, List, NamedTuple, Optional, Tuple
  import tensorflow
  from check_shapes import check_shapes, inherit_check_shapes
  from ..base import InputData, MeanAndVariance, Parameter, RegressionData, TensorType
  from ..config import default_float, default_int
  from ..covariances import Kuf
  from ..utilities import add_noise_cov, assert_params_false, to_default_float
  from .sgpr import SGPR
label_desc: Use image node_id 2 for calling the CGLB obj's underlying member method code with example usage: obj.aux_vec() and returns: self