code: def test_added_loss_term_batch(self):
      prior_dist = MultivariateNormal(
          torch.zeros(2, 5),
          DiagLinearOperator(
              torch.tensor(
                  [[1.0, 1.0, 1.0, 1.0, 1.0], [1.0, 1.0, 1.0, 1.0, 1.0]]
              )
          ),
      )
      variational_dist = MultivariateNormal(
          torch.zeros(2, 5),
          DiagLinearOperator(
              torch.tensor(
                  [
                      [0.6, 0.7, 0.8, 0.9, 1.0],
                      [0.8, 0.85, 0.9, 0.95, 1.0],
                  ]
              )
          ),
      )
      likelihood = GaussianLikelihood(batch_shape=torch.Size([3, 1]))
      likelihood.noise = torch.Tensor([[0.01], [0.1], [1.0]])
  
      added_loss_term = InducingPointKernelAddedLossTerm(
          prior_dist, variational_dist, likelihood
      )
      self.assertAllClose(
          added_loss_term.loss(),
          torch.tensor([[-50.0, -25.0], [-5.0, -2.5], [-0.5, -0.25]]),
      )
  
file_path: gpytorch/test/mlls/test_inducing_point_kernel_added_loss_term.py
imports: import unittest
  import torch
  from linear_operator.operators import DiagLinearOperator
  from gpytorch.distributions import MultivariateNormal
  from gpytorch.likelihoods import GaussianLikelihood
  from gpytorch.mlls import InducingPointKernelAddedLossTerm
  from gpytorch.test.base_test_case import BaseTestCase
label_desc: Use image node_id 2 for calling the TestInducingPointKernelAddedLossTerm obj's underlying member method code with example usage: obj.test_added_loss_term_batch() without return types