code: def test_backward(self):
      inputs = nn.Parameter(
          torch.tensor([-6, -5, -3, -1, 0, 1, 3, 5], dtype=torch.float)
      )
      output = gpytorch.log_normal_cdf(inputs)
      output.backward(torch.ones(8))
  
      gradient = inputs.grad
      expected_gradient = torch.tensor(
          [
              6.1585,
              5.1865,
              3.2831,
              1.5251,
              0.7979,
              0.2876,
              0.0044,
              0.0000,
          ],
          dtype=torch.float,
      )
  
      # Should be reasonable for small values
      for d in torch.abs(gradient[:3] - expected_gradient[:3]):
          self.assertLess(d, 5e-1)
  
      # Should be very accurate for larger ones
      for d in torch.abs(gradient[3:] - expected_gradient[3:]):
          self.assertLess(d, 5e-4)
  
file_path: gpytorch/test/functions/test_log_normal_cdf.py
imports: import math
  import unittest
  import torch
  from torch import nn
  import gpytorch
label_desc: Use image node_id 2 for calling the TestLogNormalCDF obj's underlying member method code with example usage: obj.test_backward() without return types