code: def test_intractable_smoke(backend):
      def model():
          i_plate = pyro.plate("i", 2, dim=-1)
          j_plate = pyro.plate("j", 3, dim=-2)
          with i_plate:
              a = pyro.sample("a", dist.Normal(0, 1))
          with j_plate:
              b = pyro.sample("b", dist.Normal(0, 1))
          with i_plate, j_plate:
              c = pyro.sample("c", dist.Normal(a + b, 1))
              pyro.sample("d", dist.Normal(c, 1), obs=torch.zeros(3, 2))
  
      guide = AutoGaussian(model, backend=backend)
      svi = SVI(model, guide, ClippedAdam({"lr": 1e-8}), Trace_ELBO())
      for step in range(2):
          with xfail_if_not_implemented():
              svi.step()
      guide()
      predictive = Predictive(model, guide=guide, num_samples=2)
      predictive()
  
imports: from collections import OrderedDict, namedtuple
  import pytest
  import torch
  import pyro
  import pyro.distributions
  import pyro.poutine
  from pyro.infer import SVI, JitTrace_ELBO, Predictive, Trace_ELBO
  from pyro.infer.autoguide import AutoGaussian, AutoGuideList
  from pyro.infer.autoguide.gaussian import AutoGaussianDense, AutoGaussianFunsor, _break_plates
  from pyro.infer.reparam import LocScaleReparam
  from pyro.optim import ClippedAdam
  from tests.common import assert_close, assert_equal, xfail_if_not_implemented
label_desc: Use image node_id 15 for calling a global function with example usage: test_intractable_smoke(backend) without return types