code: def test_kernel_getitem_double_batch(self):
      x = self.create_data_double_batch()
      kernel = self.create_kernel(
          num_dims=x.size(-1), batch_shape=torch.Size([3, 2])
      )
  
      res1 = kernel(x).to_dense()[
          0, 1
      ]  # Result of first kernel on first batch of data
  
      new_kernel = kernel[0, 1]
      res2 = new_kernel(
          x[0, 1]
      ).to_dense()  # Should also be result of first kernel on first batch of data.
  
      self.assertLess(torch.norm(res1 - res2) / res1.norm(), 1e-4)
  
      # Test diagonal
      kernel_diag = kernel(x, diag=True)
      actual_diag = res1.diagonal(dim1=-1, dim2=-2)
      self.assertLess(
          torch.norm(kernel_diag - actual_diag) / actual_diag.norm(),
          1e-4,
      )
  
file_path: gpytorch/test/kernels/test_spectral_mixture_kernel.py
imports: import unittest
  import torch
  from gpytorch.kernels import SpectralMixtureKernel
label_desc: Use image node_id 11 for calling the TestSpectralMixtureKernel obj's underlying member method code with example usage: obj.test_kernel_getitem_double_batch() without return types