code: def test_survival_function():
      random = numpy.random.default_rng(0xDEADBEEF)
  
      batch_size = 32
  
      loc = torch.tensor(
          numpy.array([random.standard_normal(batch_size)])
      )
  
      scale = torch.tensor(
          numpy.array([random.random(batch_size) + 1.0])
      )
  
      x = torch.linspace(-8.0, 8.0, batch_size).to(torch.float64)
  
      torch.testing.assert_close(
          survival_function(x, Normal(loc, scale)),
          torch.tensor(
              scipy.stats.norm(loc, scale).sf(x), dtype=torch.float32
          ),
      )
  
imports: import numpy
  import scipy.stats
  import torch
  import torch.testing
  from torch.distributions import Normal
  from neuralcompression.functional import survival_function
label_desc: Use image node_id 1 for calling a global function with example usage: test_survival_function() without return types