code: def set_device_based_on_group(group: ProcessGroup) -> None:
      # torch.cuda.set_device(group.rank() % torch.cuda.device_count())
      torch.cuda.set_device(
          torch.distributed.get_rank() % torch.cuda.device_count()
      )
  
imports: from threading import Event, Lock, Thread
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union, cast
  import torch
  from torch import nn
  from torch.distributed import ProcessGroup, rpc
  from torch.distributed.distributed_c10d import _get_global_rank
  from fairscale.nn.model_parallel.initialize import get_pipeline_parallel_group
  from .async_pipe import AsyncPipe
  from .types import EVENT_LOOP_QUEUE, PipeMessage, TensorOrTensors
label_desc: Use image node_id 1 for calling a global function with example usage: set_device_based_on_group(group) without return types