code: def test_deep_to_pyro_module(dtype):
      class ExampleModule(PyroModule):
          def __init__(self):
              super().__init__()
              self.a = torch.nn.Parameter(torch.zeros(2))
              self.register_buffer("b", torch.zeros(3))
              self.c = torch.randn(
                  4
              )  # this wouldn't work with torch.nn.Module.to()
              self.d = dist.Normal(0, 1)
              self.e = PyroParam(
                  torch.randn(()),
                  constraint=constraints.greater_than(
                      torch.tensor(0.5)
                  ),
              )
              self.f = PyroSample(dist.Normal(0, 1))
              self.g = PyroSample(lambda self: dist.Normal(self.f, 1))
  
      module = ExampleModule()
      module = deep_to(module, dtype=dtype)
      assert isinstance(module, ExampleModule)
      assert module.a.dtype == dtype
      assert module.b.dtype == dtype
      assert module.c.dtype == dtype
      assert module.d.loc.dtype == dtype
      assert module.d.scale.dtype == dtype
      assert module._pyro_params["e"][0].lower_bound.dtype == dtype
      assert module.e.dtype == dtype
      assert module.f.dtype == dtype
      assert module.g.dtype == dtype
  
imports: import weakref
  import numpy
  import pytest
  import torch
  from torch.autograd import grad
  import pyro.distributions
  from pyro.distributions import constraints
  from pyro.distributions.util import broadcast_shape, deep_to, detach, sum_leftmost, sum_rightmost, weakmethod
  from pyro.nn.module import PyroModule, PyroParam, PyroSample
  from tests.common import assert_equal
label_desc: Use image node_id 18 for calling a global function with example usage: test_deep_to_pyro_module(dtype) without return types