code: def univariate_log_marginal_likelihood(
      y: AnyNDArray, K: AnyNDArray, noise_var: AnyNDArray
  ) -> AnyNDArray:
      return (  # type: ignore[no-any-return]
          -0.5 * y * y / (K + noise_var)
          - 0.5 * np.log(K + noise_var)
          - 0.5 * np.log(np.pi * 2.0)
      )
  
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 1 for calling a global function with example usage: univariate_log_marginal_likelihood(y, K, noise_var) and returns: unknown