code: def xi_to_meanvarsqrt(xi1: tf.Tensor, xi2: tf.Tensor) -> tf.Tensor:
      return gpflow.optimizers.natgrad.expectation_to_meanvarsqrt(
          xi1, xi2
      )
  
imports: from typing import Any, Optional, Tuple
  import numpy
  import pytest
  import tensorflow
  from check_shapes import check_shapes
  import gpflow
  from gpflow import set_trainable
  from gpflow.config import default_float
  from gpflow.kernels import Kernel, SquaredExponential
  from gpflow.likelihoods import Gaussian, Likelihood
  from gpflow.models import GPR, SGPR, SVGP, VGP, BayesianModel
  from gpflow.optimizers import NaturalGradient
label_desc: Use image node_id 2 for calling the XiEta obj's underlying member method code with example usage: obj.xi_to_meanvarsqrt(xi1, xi2) and returns: gpflow