code: def test_double_precision_ddp(tmpdir):
      model = DoublePrecisionBoringModel()
  
      trainer = Trainer(
          max_epochs=1,
          default_root_dir=tmpdir,
          strategy="ddp_spawn",
          accelerator="gpu",
          devices=2,
          fast_dev_run=2,
          precision="64-true",
          log_every_n_steps=1,
      )
      trainer.fit(model)
      trainer.validate(model)
  
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 2 for calling a global function with example usage: test_double_precision_ddp(tmpdir) without return types