code: def test_montecarlo_predict_log_density(
      likelihood_var: float,
      x: TensorType,
      mu: TensorType,
      var: TensorType,
      y: TensorType,
  ) -> None:
      (
          likelihood_gaussian_mc,
          likelihood_gaussian,
      ) = _make_montecarlo_likelihoods(likelihood_var)
      assert_allclose(
          likelihood_gaussian_mc.predict_log_density(x, mu, var, y),
          likelihood_gaussian.predict_log_density(x, mu, var, y),
          rtol=5e-4,
          atol=1e-4,
      )
  
imports: from typing import Sequence, Tuple
  import numpy
  import pytest
  import tensorflow
  from numpy.testing import assert_allclose
  import gpflow
  import gpflow.ci_utils
  from gpflow.base import TensorType
  from gpflow.config import default_float, default_int
  from gpflow.likelihoods import HeteroskedasticTFPConditional, Likelihood, MonteCarloLikelihood, MultiLatentLikelihood, MultiLatentTFPConditional, QuadratureLikelihood, ScalarLikelihood, Bernoulli, Beta, Exponential, Gamma, Gaussian, GaussianMC, MultiClass, Ordinal, Poisson, StudentT
label_desc: Use image node_id 12 for calling a global function with example usage: test_montecarlo_predict_log_density(likelihood_var, x, mu, var, y) without return types