code: def _create_marginal_input(self, batch_shape=torch.Size()):
      mat = torch.randn(*batch_shape, 5, 5)
      eye = torch.diag_embed(torch.ones(*batch_shape, 5))
      return MultivariateNormal(
          torch.randn(*batch_shape, 5),
          mat @ mat.transpose(-1, -2) + eye,
      )
  
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 3 for calling the BaseLikelihoodTestCase obj's underlying member method code with example usage: obj._create_marginal_input(batch_shape) and returns: MultivariateNormal