code: def test_deep_to_structure(dtype):
      data = [
          None,
          True,
          "foo",
          1.0,
          {False},
          torch.tensor(0.0),
          (torch.tensor(1.0), torch.tensor([2.0, 3.0])),
          [torch.tensor(4.0)],
          {"bar": torch.tensor(5.0)},
      ]
      actual = deep_to(data)
      expected = [
          None,
          True,
          "foo",
          1.0,
          {False},
          torch.tensor(0.0).to(dtype),
          (
              torch.tensor(1.0).to(dtype),
              torch.tensor([2.0, 3.0]).to(dtype),
          ),
          [torch.tensor(4.0).to(dtype)],
          {"bar": torch.tensor(5.0).to(dtype)},
      ]
      assert_equal(actual, expected)
  
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 15 for calling a global function with example usage: test_deep_to_structure(dtype) without return types