code: def test_batch(self):
      a = torch.tensor([[4, 2, 8], [1, 2, 3]], dtype=torch.float).view(
          2, 3, 1
      )
      b = torch.tensor([[0, 2, 1], [-1, 2, 0]], dtype=torch.float).view(
          2, 3, 1
      )
      period = torch.tensor(1, dtype=torch.float).view(1, 1, 1)
      kernel = CosineKernel().initialize(period_length=period)
      kernel.eval()
  
      actual = torch.zeros(2, 3, 3)
      for k in range(2):
          for i in range(3):
              for j in range(3):
                  actual[k, i, j] = torch.cos(
                      math.pi * ((a[k, i] - b[k, j]) / period)
                  )
  
      res = kernel(a, b).to_dense()
      self.assertLess(torch.norm(res - actual), 1e-5)
  
file_path: gpytorch/test/kernels/test_cosine_kernel.py
imports: import math
  import unittest
  import torch
  from gpytorch.kernels import CosineKernel
  from gpytorch.priors import NormalPrior
label_desc: Use image node_id 2 for calling the TestCosineKernel obj's underlying member method code with example usage: obj.test_batch() without return types