code: def test_ard_batch(self):
      a = torch.tensor(
          [[[1, 2, 3], [2, 4, 3]], [[2, -1, 2], [2, -1, 0]]],
          dtype=torch.float,
      )
      b = torch.tensor([[[1, 4, 3]], [[2, -1, 0]]], dtype=torch.float)
      lengthscales = torch.tensor([[[1, 2, 1]]], dtype=torch.float)
  
      kernel = MaternKernel(
          nu=2.5, batch_shape=torch.Size([2]), ard_num_dims=3
      )
      kernel.initialize(lengthscale=lengthscales)
      kernel.eval()
  
      dist = torch.tensor(
          [[[1], [1]], [[2], [0]]], dtype=torch.float
      ).mul_(math.sqrt(5))
      actual = (dist**2 / 3 + dist + 1).mul(torch.exp(-dist))
      res = kernel(a, b).to_dense()
      self.assertLess(torch.norm(res - actual), 1e-3)
  
imports: import math
  import pickle
  import unittest
  import torch
  from gpytorch.kernels import MaternKernel
  from gpytorch.priors import NormalPrior
  from gpytorch.test.base_kernel_test_case import BaseKernelTestCase
label_desc: Use image node_id 7 for calling the TestMaternKernel obj's underlying member method code with example usage: obj.test_ard_batch() without return types