code: def univariate_posterior(
      y: AnyNDArray, K: AnyNDArray, noise_var: AnyNDArray
  ) -> Tuple[AnyNDArray, AnyNDArray]:
      mean = K * y / (K + noise_var)
      variance: AnyNDArray = K - K / (K + noise_var)
      return mean, variance
  
imports: from typing import Tuple, cast
  import numpy
  import pytest
  from check_shapes import check_shapes
  from numpy.testing import assert_allclose
  import gpflow
  from gpflow.base import AnyNDArray
  from gpflow.kernels import SquaredExponential
  from gpflow.likelihoods import Gaussian
  from tests.gpflow.kernels.reference import ref_rbf_kernel
label_desc: Use image node_id 2 for calling a global function with example usage: univariate_posterior(y, K, noise_var) and returns: mean,  variance