code: def test_forward(self):
      inputs = torch.tensor(
          [-6, -5, -3, -1, 0, 1, 3, 5], dtype=torch.float
      )
      output = gpytorch.log_normal_cdf(inputs)
  
      # Answers should be reasonable for small values
      self.assertLess(math.fabs(output[0] + 20.7368), 1e-4)
      self.assertLess(math.fabs(output[1] + 15), 0.1)
      self.assertLess(math.fabs(output[2] + 6.6), 0.01)
      self.assertLess(math.fabs(output[3] + 1.841), 0.001)
  
      # Should be very accurate for positive values
      self.assertLess(math.fabs(output[4] + 0.693147), 1e-4)
      self.assertLess(math.fabs(output[5] + 0.1727), 1e-4)
      self.assertLess(math.fabs(output[6] + 0.00135081), 1e-4)
      self.assertLess(math.fabs(output[7] + 2.86652e-7), 1e-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 1 for calling the TestLogNormalCDF obj's underlying member method code with example usage: obj.test_forward() without return types