class_docstr: Strategy for training with multiple processes in parallel.
class_docstr_tok: ["Strategy","for","training","with","multiple","processes","in","parallel","."]
code: def global_rank(self) -> int:
      return (
          self.cluster_environment.global_rank()
          if self.cluster_environment is not None
          else 0
      )
  
imports: from abc import ABC
  from typing import Any, Dict, List, Optional
  import torch
  from torch import Tensor
  from typing_extensions import override
  from lightning.fabric.accelerators.accelerator import Accelerator
  from lightning.fabric.plugins.environments.cluster_environment import ClusterEnvironment
  from lightning.fabric.plugins.io.checkpoint_io import CheckpointIO
  from lightning.fabric.plugins.precision import Precision
  from lightning.fabric.strategies.strategy import Strategy
  from lightning.fabric.utilities.distributed import _all_gather_ddp_if_available
  from lightning.fabric.utilities.types import ReduceOp
label_desc: Use image node_id 2 for calling the ParallelStrategy obj's underlying member method code with example usage: obj.global_rank() and returns: unknown