code: def test_convert_module():
      plugin = DoublePrecision()
      model = BoringModel()
      assert (
          model.layer.weight.dtype
          == model.layer.bias.dtype
          == torch.float32
      )
      model = plugin.convert_module(model)
      assert (
          model.layer.weight.dtype
          == model.layer.bias.dtype
          == torch.float64
      )
  
imports: import pickle
  from unittest.mock import MagicMock
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
  from lightning.pytorch.plugins.precision.double import DoublePrecision
  from torch.utils.data import DataLoader, Dataset
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 4 for calling a global function with example usage: test_convert_module() without return types