code: def forward(self, x):
      if self.fail_arithmetic:
          raise ArithmeticError()
      return gpytorch.distributions.MultivariateNormal(
          torch.tensor([-3.0]), torch.tensor([[2.0]])
      )
  
file_path: gpytorch/test/likelihoods/test_noise_models.py
imports: import unittest
  import torch
  import gpytorch
  from gpytorch.likelihoods import HeteroskedasticNoise
label_desc: Use image node_id 3 for calling the NumericallyUnstableModelExample obj's underlying member method code with example usage: obj.forward(x) and returns: gpytorch