code: def bernoulli_normal_model():
      bern_0 = pyro.sample(
          "bern_0", dist.Bernoulli(torch.zeros(1) * 1e-2)
      )
      loc = torch.ones(1) if bern_0.item() else -torch.ones(1)
      normal_0 = torch.ones(1)
      pyro.sample(
          "normal_0",
          dist.Normal(loc, torch.ones(1) * 1e-2),
          obs=normal_0,
      )
      return [bern_0, normal_0]
  
file_path: pyro/tests/poutine/test_properties.py
imports: import pytest
  import torch
  import pyro
  import pyro.distributions
  import pyro.poutine
  from pyro.util import set_rng_seed
  from tests.common import assert_equal
label_desc: Use image node_id 5 for calling a global function with example usage: bernoulli_normal_model() and returns: list