code: def test_mean_and_var(self):
      torch_samples = [
          dist.Delta(self.v).sample().detach().cpu().numpy()
          for _ in range(self.n_samples)
      ]
      torch_mean = np.mean(torch_samples)
      torch_var = np.var(torch_samples)
      self.assertEqual(torch_mean, self.analytic_mean)
      self.assertEqual(torch_var, self.analytic_var)
  
file_path: gpytorch/test/distributions/test_delta.py
imports: import unittest
  import numpy
  import torch
  import gpytorch.distributions
  from gpytorch.test.base_test_case import BaseTestCase
label_desc: Use image node_id 5 for calling the TestDelta obj's underlying member method code with example usage: obj.test_mean_and_var() without return types