code: def diamond_model(dim):
      p0 = torch.tensor(math.exp(-0.20), requires_grad=True)
      p1 = torch.tensor(math.exp(-0.33), requires_grad=True)
      pyro.sample("a1", dist.Bernoulli(p0))
      pyro.sample("c1", dist.Bernoulli(p1))
      for i in pyro.plate("plate", 2):
          b_i = pyro.sample("b{}".format(i), dist.Bernoulli(p0 * p1))
          assert b_i.shape == ()
      pyro.sample("obs", dist.Bernoulli(p0), obs=torch.tensor(1.0))
  
imports: import math
  from collections import defaultdict
  import pytest
  import torch
  import pyro
  import pyro.distributions
  import pyro.poutine
  from pyro.infer.tracegraph_elbo import TrackNonReparam, _compute_downstream_costs
  from pyro.infer.util import MultiFrameTensor, get_plate_stacks
  from pyro.ops.provenance import get_provenance
  from pyro.poutine.util import prune_subsample_sites
  from tests.common import assert_equal
label_desc: Use image node_id 5 for calling a global function with example usage: diamond_model(dim) without return types