code: def test_single_batch_kernel_single_batch_x(self):
      x = self.create_data_single_batch()
      kernel = self.create_kernel(
          num_dims=x.size(-1), batch_shape=torch.Size([])
      )
      y = torch.randn_like(x[..., 0])
      kernel.initialize_from_data(x, y)
      kernel.initialize_from_data_empspect(x, y)
      batch_covar_mat = kernel(x).evaluate_kernel().to_dense()
  
      actual_mat_1 = kernel(x[0]).evaluate_kernel().to_dense()
      actual_mat_2 = kernel(x[1]).evaluate_kernel().to_dense()
      actual_covar_mat = torch.cat(
          [actual_mat_1.unsqueeze(0), actual_mat_2.unsqueeze(0)]
      )
  
      self.assertLess(
          torch.norm(batch_covar_mat - actual_covar_mat)
          / actual_covar_mat.norm(),
          1e-4,
      )
  
      # Test diagonal
      kernel_diag = kernel(x, diag=True)
      actual_diag = actual_covar_mat.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 8 for calling the TestSpectralMixtureKernel obj's underlying member method code with example usage: obj.test_single_batch_kernel_single_batch_x() without return types