code: def test_kernel(self, cuda=False):
      a = torch.tensor([[[1, 2], [2, 4]]], dtype=torch.float)
      b = torch.tensor([[[1, 3], [0, 4]]], dtype=torch.float)
  
      actual = torch.tensor(
          [
              [0.35321, 0, -0.73517, 0.0054977, 0.011443, -0.022886],
              [0, 0.73517, 0, -0.011443, -0.012374, 0.047633],
              [0.73517, 0, -0.79499, 0.022886, 0.047633, -0.083824],
              [0.12476, 0.25967, 0.25967, 0.015565, 0.064793, 0],
              [-0.25967, -0.2808, -0.54047, -0.064793, -0.23732, 0],
              [-0.25967, -0.54047, -0.2808, 0, 0, 0.032396],
          ]
      )
  
      kernel = RBFKernelGrad()
  
      if cuda:
          a = a.cuda()
          b = b.cuda()
          actual = actual.cuda()
          kernel = kernel.cuda()
  
      res = kernel(a, b).to_dense()
  
      self.assertLess(torch.norm(res - actual), 1e-5)
  
file_path: gpytorch/test/kernels/test_rbf_kernel_grad.py
imports: import unittest
  import torch
  from gpytorch.kernels import RBFKernelGrad
  from gpytorch.test.base_kernel_test_case import BaseKernelTestCase
label_desc: Use image node_id 3 for calling the TestRBFKernelGrad obj's underlying member method code with example usage: obj.test_kernel(cuda) without return types