code: def meanvarsqrt_to_xi(
      mean: tf.Tensor, varsqrt: tf.Tensor
  ) -> tf.Tensor:
      return gpflow.optimizers.natgrad.meanvarsqrt_to_expectation(
          mean, varsqrt
      )
  
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 1 for calling the XiEta obj's underlying member method code with example usage: obj.meanvarsqrt_to_xi(mean, varsqrt) and returns: gpflow