code: def test_sample(self):
      a = torch.as_tensor(0.0)
      b = torch.as_tensor(1.0)
      sigma = 0.01
  
      gauss_max = 1 / (math.sqrt(2 * math.pi) * sigma)
      ratio_gaussian_mass = 1 / (gauss_max * (b - a) + 1)
  
      prior = SmoothedBoxPrior(a, b, sigma)
  
      n_samples = 50000
      samples = prior.sample((n_samples,))
  
      gaussian_idx = (samples < a) | (samples > b)
      gaussian_samples = samples[gaussian_idx]
      n_gaussian = gaussian_samples.shape[0]
  
      self.assertTrue(
          torch.all(
              approx_equal(
                  torch.as_tensor(n_gaussian / n_samples),
                  ratio_gaussian_mass,
                  epsilon=0.005,
              )
          )
      )
  
file_path: gpytorch/test/priors/test_smoothed_box_prior.py
imports: import math
  import unittest
  import torch
  from gpytorch.priors import SmoothedBoxPrior
  from gpytorch.test.utils import approx_equal, least_used_cuda_device
label_desc: Use image node_id 9 for calling the TestSmoothedBoxPrior obj's underlying member method code with example usage: obj.test_sample() without return types