code: def _make_montecarlo_likelihoods(
      var: float,
  ) -> Tuple[GaussianMC, Gaussian]:
      gaussian_mc_likelihood = GaussianMC(var)
      gaussian_mc_likelihood.num_monte_carlo_points = 1000000
      return gaussian_mc_likelihood, Gaussian(var)
  
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 10 for calling a global function with example usage: _make_montecarlo_likelihoods(var) and returns: gaussian_mc_likelihood,  Gaussian