class_docstr: A DDP Strategy which uses ray as backend.
class_docstr_tok: ["A","DDP","Strategy","which","uses","ray","as","backend","."]
docstr: Set the appropriate rank attribues for the trainer.
docstr_tok: ["Set","the","appropriate","rank","attribues","for","the","trainer","."]
code: def set_world_ranks(self, process_idx: int = 0):
      """Set the appropriate rank attribues for the trainer."""
      invalidInputError(
          self.cluster_environment is not None
          and isinstance(self.cluster_environment, RayEnvironment),
          "expect ray environment here",
      )
      if self.cluster_environment.is_remote():  # type: ignore
          self._local_rank = self.global_to_local[self.global_rank]  # type: ignore
          self.cluster_environment.set_global_rank(self.global_rank)
          self.cluster_environment.set_world_size(self.num_workers)
          rank_zero_only.rank = self.cluster_environment.global_rank()
  
imports: import os
  import warnings
  from typing import Callable, Dict, List, Union, Any, Optional
  from collections import defaultdict
  import ray
  from ray.util.ml_utils.util import find_free_port
  import torch
  from torch.optim.lr_scheduler import _LRScheduler
  from torch.nn.parallel.distributed import DistributedDataParallel
  import pytorch_lightning
  from pytorch_lightning.core.datamodule import LightningDataModule
  from pytorch_lightning.trainer.states import TrainerFn
  from pytorch_lightning.utilities import rank_zero_only
  from pytorch_lightning.utilities.apply_func import move_data_to_device
  from pytorch_lightning.strategies.launchers import _SpawnLauncher
  from pytorch_lightning.strategies import DDPSpawnStrategy
  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.core.optimizer import LightningOptimizer
  from .ray_envbase import RayEnvironment
  from bigdl.nano.utils.common import invalidInputError
  from bigdl.nano.utils.pytorch import TORCH_VERSION_LESS_1_12
  from bigdl.nano.deps.ipex.ipex_api import ipex_optimize
  from bigdl.nano.pytorch.dispatcher import _get_patch_status
label_desc: Use image node_id 6 for calling the RayStrategy obj's underlying member method code with example usage: obj.set_world_ranks(process_idx) without return types