code: def test_mixin_factory():
      assert PyroModule[nn.Module] is PyroModule
      assert PyroModule[PyroModule] is PyroModule
  
      module = PyroModule[nn.Sequential](
          PyroModule[nn.Linear](28 * 28, 200),
          PyroModule[nn.Sigmoid](),
          PyroModule[nn.Linear](200, 200),
          PyroModule[nn.Sigmoid](),
          PyroModule[nn.Linear](200, 10),
      )
  
      assert isinstance(module, nn.Sequential)
      assert isinstance(module, PyroModule)
      assert type(module).__name__ == "PyroSequential"
      assert PyroModule[type(module)] is type(module)
  
      assert isinstance(module[0], nn.Linear)
      assert isinstance(module[0], PyroModule)
      assert type(module[0]).__name__ == "PyroLinear"
      assert type(module[2]) is type(module[0])  # noqa: E721
      assert module[0]._pyro_name == "0"
      assert module[1]._pyro_name == "1"
  
      # Ensure new types are serializable.
      data = torch.randn(28 * 28)
      expected = module(data)
      with warnings.catch_warnings():
          warnings.filterwarnings("ignore", category=UserWarning)
          f = io.BytesIO()
          torch.save(module, f)
          del module
          pyro.clear_param_store()
          f.seek(0)
          module = torch.load(f)
      assert type(module).__name__ == "PyroSequential"
      actual = module(data)
      assert_equal(actual, expected)
  
imports: import io
  import warnings
  import pytest
  import torch
  from torch import nn
  from torch.distributions import constraints, transform_to
  import pyro
  import pyro.distributions
  from pyro import poutine
  from pyro.infer import SVI, Trace_ELBO
  from pyro.nn.module import PyroModule, PyroParam, PyroSample, clear, to_pyro_module_
  from pyro.optim import Adam
  from tests.common import assert_equal
label_desc: Use image node_id 15 for calling a global function with example usage: test_mixin_factory() without return types