class_docstr: Sparse GP regression.
  
  The key reference is :cite:t:`titsias2009variational`.
  
  For a use example see :doc:`../../../../notebooks/getting_started/large_data`.
docstr: Matrices used in log-det calculation
  
  :return:
      * :math:`σ²`,
      * :math:`σ`,
      * :math:`A = L⁻¹K_{uf}/σ`, where :math:`LLᵀ = Kᵤᵤ`,
      * :math:`B = AAT+I`,
      * :math:`LB` where :math`LBLBᵀ = B`,
      * :math:`AAT = AAᵀ`,
docstr_tok: ["Matrices","used","in","log-det","calculation",":","return",":","*",":","math",":","`","\u03c3\u00b2","`",",","*",":","math",":","`","\u03c3","`",",","*",":","math",":","`","A","=","L\u207b\u00b9K_","{","uf","}","\/\u03c3","`",",","where",":","math",":","`","LL\u1d40","=","K\u1d64\u1d64","`",",","*",":","math",":","`","B","=","AAT+I","`",",","*",":","math",":","`","LB","`","where",":","math","`","LBLB\u1d40","=","B","`",",","*",":","math",":","`","AAT","=","AA\u1d40","`",","]
code: def _common_calculation(self) -> "SGPR.CommonTensors":
      """
      Matrices used in log-det calculation
  
      :return:
          * :math:`σ²`,
          * :math:`σ`,
          * :math:`A = L⁻¹K_{uf}/σ`, where :math:`LLᵀ = Kᵤᵤ`,
          * :math:`B = AAT+I`,
          * :math:`LB` where :math`LBLBᵀ = B`,
          * :math:`AAT = AAᵀ`,
      """
      x, _ = self.data  # [N]
      iv = self.inducing_variable  # [M]
  
      sigma_sq = tf.squeeze(
          self.likelihood.variance_at(x), axis=-1
      )  # [N]
      sigma = tf.sqrt(sigma_sq)  # [N]
  
      kuf = Kuf(iv, self.kernel, x)  # [M, N]
      kuu = Kuu(iv, self.kernel, jitter=default_jitter())  # [M, M]
      L = tf.linalg.cholesky(kuu)  # [M, M]
  
      # Compute intermediate matrices
      A = tf.linalg.triangular_solve(L, kuf / sigma, lower=True)
      AAT = tf.linalg.matmul(A, A, transpose_b=True)
      B = add_noise_cov(AAT, tf.cast(1.0, AAT.dtype))
      LB = tf.linalg.cholesky(B)
  
      return self.CommonTensors(sigma_sq, sigma, A, B, LB, AAT, L)
  
imports: from typing import NamedTuple, Optional, Tuple
  import numpy
  import tensorflow
  from check_shapes import check_shapes, inherit_check_shapes
  from ..None import posteriors
  from ..base import InputData, MeanAndVariance, RegressionData, TensorData
  from ..config import default_float, default_jitter
  from ..covariances.dispatch import Kuf, Kuu
  from ..inducing_variables import InducingPoints
  from ..kernels import Kernel
  from ..likelihoods import Gaussian
  from ..mean_functions import MeanFunction
  from ..utilities import add_noise_cov, assert_params_false, to_default_float
  from .model import GPModel
  from .training_mixins import InternalDataTrainingLossMixin
  from .util import InducingPointsLike, data_input_to_tensor, inducingpoint_wrapper
label_desc: Use image node_id 2 for calling the SGPR_deprecated obj's underlying member method code with example usage: obj._common_calculation() and returns: self