code: def _test_marginal(self, batch_shape):
      likelihood = self.create_likelihood()
      likelihood.max_plate_nesting += len(batch_shape)
      input = self._create_marginal_input(batch_shape)
      output = likelihood(input)
  
      self.assertTrue(isinstance(output, Distribution))
      self.assertEqual(
          output.sample().shape[-len(input.sample().shape) :],
          input.sample().shape,
      )
  
      # Compare against default implementation
      with gpytorch.settings.num_likelihood_samples(30000):
          default = Likelihood.marginal(likelihood, input)
      # print(output.mean, default.mean)
      default_mean = default.mean
      actual_mean = output.mean
      if default_mean.dim() > actual_mean.dim():
          default_mean = default_mean.mean(0)
      self.assertAllClose(
          default_mean, actual_mean, rtol=0.25, atol=0.25
      )
  
file_path: gpytorch/gpytorch/test/base_likelihood_test_case.py
imports: from abc import abstractmethod
  import torch
  from torch.distributions import Distribution
  import gpytorch
  from gpytorch.distributions import MultivariateNormal
  from gpytorch.likelihoods import Likelihood
  from .base_test_case import BaseTestCase
label_desc: Use image node_id 8 for calling the BaseLikelihoodTestCase obj's underlying member method code with example usage: obj._test_marginal(batch_shape) without return types