code: def test_diag_calculation(self):
      a = torch.tensor([0.1, 0.2]).view(2, 1)
      b = torch.tensor([0.2, 0.4]).view(2, 1)
      power = 1
      offset = 1
  
      kernel = DownsamplingKernel()
      kernel.initialize(power=power, offset=offset)
      kernel.eval()
  
      diff = torch.tensor([[0.72, 0.54], [0.64, 0.48]])
      actual = offset + diff.pow(1 + power)
      res = kernel(a, b, diag=True)
  
      self.assertLess(torch.linalg.norm(res - torch.diag(actual)), 1e-5)
  
imports: import torch
  from botorch.models.kernels.downsampling import DownsamplingKernel
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.priors.torch_priors import GammaPrior, NormalPrior
  from gpytorch.test.base_kernel_test_case import BaseKernelTestCase
label_desc: Use image node_id 16 for calling the TestDownsamplingKernel obj's underlying member method code with example usage: obj.test_diag_calculation() without return types