code: def test_amp_gpus_ddp_fork():
      """Ensure the use of AMP with `ddp_fork` (or associated alias strategies) does not generate CUDA initialization
      errors."""
      _ = MixedPrecision(precision="16-mixed", device="cuda")
      with multiprocessing.get_context("fork").Pool(1) as pool:
          in_bad_fork = pool.apply(torch.cuda._is_in_bad_fork)
      assert not in_bad_fork
  
imports: import multiprocessing
  import torch
  from lightning.pytorch.plugins import MixedPrecision
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 1 for calling a global function with example usage: test_amp_gpus_ddp_fork() without return types