code: def test_get_model_relations(include_deterministic):
      def model(data):
          a = pyro.sample("a", dist.Normal(0, 1))
          b = pyro.sample("b", dist.Normal(a, 1))
          c = pyro.sample("c", dist.Normal(a, b.exp()))
          d = pyro.sample(
              "d", dist.Bernoulli(logits=c), obs=torch.tensor(0.0)
          )
  
          with pyro.plate("p", len(data)):
              e = pyro.sample("e", dist.Normal(a, b.exp()))
              f = pyro.deterministic("f", e + 1)
              g = pyro.sample("g", dist.Delta(e + 1), obs=e + 1)
              h = pyro.sample("h", dist.Delta(e + 1))
              i = pyro.sample(
                  "i", dist.Normal(e, (f + g + h).exp()), obs=data
              )
  
          return [a, b, c, d, e, f, g, h, i]
  
      data = torch.randn(3)
      actual = get_model_relations(
          model,
          (data,),
          include_deterministic=include_deterministic,
      )
  
      if include_deterministic:
          expected = {
              "observed": ["d", "f", "g", "i"],
              "param_constraint": {},
              "plate_sample": {"p": ["e", "f", "g", "h", "i"]},
              "sample_dist": {
                  "a": "Normal",
                  "b": "Normal",
                  "c": "Normal",
                  "d": "Bernoulli",
                  "e": "Normal",
                  "f": "Deterministic",
                  "g": "Delta",
                  "h": "Delta",
                  "i": "Normal",
              },
              "sample_param": {
                  "a": [],
                  "b": [],
                  "c": [],
                  "d": [],
                  "e": [],
                  "f": [],
                  "g": [],
                  "h": [],
                  "i": [],
              },
              "sample_sample": {
                  "a": [],
                  "b": ["a"],
                  "c": ["a", "b"],
                  "d": ["c"],
                  "e": ["a", "b"],
                  "f": ["e"],
                  "g": ["e"],
                  "h": ["e"],
                  "i": ["e", "f", "g", "h"],
              },
          }
      else:
          expected = {
              "sample_sample": {
                  "a": [],
                  "b": ["a"],
                  "c": ["a", "b"],
                  "d": ["c"],
                  "e": ["a", "b"],
                  "f": ["e"],
                  "g": ["e"],
                  "h": ["e"],
                  "i": ["e"],
              },
              "sample_param": {
                  "a": [],
                  "b": [],
                  "c": [],
                  "d": [],
                  "e": [],
                  "f": [],
                  "g": [],
                  "h": [],
                  "i": [],
              },
              "sample_dist": {
                  "a": "Normal",
                  "b": "Normal",
                  "c": "Normal",
                  "d": "Bernoulli",
                  "e": "Normal",
                  "f": "Deterministic",
                  "g": "Delta",
                  "h": "Delta",
                  "i": "Normal",
              },
              "param_constraint": {},
              "plate_sample": {"p": ["e", "f", "g", "h", "i"]},
              "observed": ["d", "f", "g", "i"],
          }
  
      assert actual == expected
  
imports: import pytest
  import torch
  import pyro
  import pyro.distributions
  from pyro.distributions.testing.fakes import NonreparameterizedNormal
  from pyro.infer.inspect import _deep_merge, get_dependencies, get_model_relations
label_desc: Use image node_id 15 for calling a global function with example usage: test_get_model_relations(include_deterministic) and returns: list