code: def test_1_2_backward(self):
      nu = 1 / 2
      batch_size = (3, 2, 4)
      x1 = torch.randn(*batch_size, 7, 9, dtype=torch.float64)
      x2 = torch.randn(*batch_size, 6, 9, dtype=torch.float64)
      lengthscale = (
          torch.randn(
              *batch_size, dtype=torch.float64, requires_grad=True
          ).view(*batch_size, 1, 1)
          ** 2
      )
      f = lambda x1, x2, l: gpytorch.functions.MaternCovariance.apply(
          x1, x2, l, nu, dist_func
      )
      try:
          torch.autograd.gradcheck(f, (x1, x2, lengthscale))
      except RuntimeError:
          self.fail("Gradcheck failed")
  
file_path: gpytorch/test/functions/test_matern_covariance.py
imports: import math
  import unittest
  import torch
  import gpytorch
label_desc: Use image node_id 2 for calling the TestMaternCovariance obj's underlying member method code with example usage: obj.test_1_2_backward() without return types