code: def __init__(self, strategy: "DDPSpawnStrategy") -> None:  # type: ignore[override]
      self._strategy: DDPSpawnStrategy = strategy
      self._start_method = "spawn"
  
imports: import os
  import copy
  import multiprocessing
  from typing import Any, List, Optional, Callable
  import torch
  from torch import nn
  from torch.multiprocessing.spawn import ProcessContext
  from torch.nn.parallel.distributed import DistributedDataParallel
  from torch.optim.lr_scheduler import _LRScheduler
  import pytorch_lightning
  from pytorch_lightning.trainer.states import TrainerFn
  from pytorch_lightning.core.optimizer import LightningOptimizer
  from pytorch_lightning.core.optimizer import _configure_schedulers_automatic_opt
  from pytorch_lightning.core.optimizer import _configure_schedulers_manual_opt
  from pytorch_lightning.core.optimizer import _set_scheduler_opt_idx, _validate_scheduler_api
  from pytorch_lightning.strategies.launchers import _SpawnLauncher
  from pytorch_lightning.strategies import DDPSpawnStrategy
  from pytorch_lightning.plugins.environments import LightningEnvironment
  from bigdl.nano.utils.common import schedule_processors
  from bigdl.nano.pytorch.dispatcher import _get_patch_status
  from bigdl.nano.deps.ipex.ipex_api import ipex_optimize
  from bigdl.nano.utils.common import invalidInputError
  from bigdl.nano.utils.common import EnvContext
  from bigdl.nano.utils.pytorch import TORCH_VERSION_LESS_1_12
  import logging
  import warnings
label_desc: Use image node_id 1 to create a new _DDPSpawnLauncher object from inherited base classes: _SpawnLauncher with example: obj = _DDPSpawnLauncher(strategy)