code: def test_ddp_kwargs_from_registry(
      strategy_name, expected_ddp_kwargs, mps_count_0
  ):
      trainer = Trainer(strategy=strategy_name)
      assert trainer.strategy._ddp_kwargs == expected_ddp_kwargs
  
file_path: pytorch-lightning/tests/tests_pytorch/strategies/test_ddp.py
imports: import os
  from datetime import timedelta
  from unittest import mock
  import pytest
  import torch
  from lightning.fabric.plugins.environments import LightningEnvironment
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_0
  from lightning.pytorch import LightningModule, Trainer
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.plugins import DoublePrecision, HalfPrecision, Precision
  from lightning.pytorch.strategies import DDPStrategy
  from lightning.pytorch.trainer.states import TrainerFn
  from torch.nn.parallel import DistributedDataParallel
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 2 for calling a global function with example usage: test_ddp_kwargs_from_registry(strategy_name, expected_ddp_kwargs, mps_count_0) without return types