code: def init_distributed(
      dist_backend=None,
      auto_mpi_discovery=True,
      distributed_port=TORCH_DISTRIBUTED_DEFAULT_PORT,
      verbose=True,
      timeout=default_pg_timeout,
      init_method=None,
      dist_init_required=None,
      config=None,
      rank=-1,
      world_size=-1,
  ):
      """Initialize dist backend, potentially performing MPI discovery if needed
  
      Arguments:
          dist_backend: Optional (str). torch distributed backend, e.g., nccl, mpi, gloo
          auto_mpi_discovery Optional (bool). if distributed environment variables are not set, attempt to discover them from MPI
          distributed_port: Optional (int). torch distributed backend port
          verbose: Optional (bool). verbose logging
          timeout: Optional (timedelta). Timeout for operations executed against the process group. Default value equals 30 minutes.
          init_method: Optional (string). Torch distributed, URL specifying how to initialize the process group. Default is “env://” if no init_method or store is specified.
          config: Optional (dict). DeepSpeed configuration for setting up comms options (e.g. Comms profiling)
          rank: Optional (int). The current manually specified rank. Some init_method like “tcp://” need the rank and world_size as well (see: https://pytorch.org/docs/stable/distributed.html#tcp-initialization)
          world_size: Optional (int). Desired world_size for the TCP or Shared file-system initialization.
      """
      global cdb
  
      configure(deepspeed_config=config)
  
      if dist_init_required is None:
          dist_init_required = cdb is None or not cdb.is_initialized()
  
      if cdb is None:
          init_deepspeed_backend(
              get_accelerator().communication_backend_name(),
              timeout,
              init_method,
          )
          set_backend()
          utils.logger.info(f"cdb={cdb}")
      if cdb is None and torch.distributed.is_initialized():
          # The user initialized torch.dist themselves, create cdb and short-circuit
          cdb = TorchBackend(dist_backend, timeout, init_method)
          return
  
      if dist_init_required is False:
          assert (
              cdb is not None and cdb.is_initialized() is True
          ), "Distributed backend is not initialized. Please set dist_init_required to True or initialize before calling deepspeed.initialize()"
      else:
          # Initialize torch distributed if needed
          required_env = [
              "RANK",
              "WORLD_SIZE",
              "MASTER_ADDR",
              "MASTER_PORT",
              "LOCAL_RANK",
          ]
          if auto_mpi_discovery and not all(
              map(lambda v: v in os.environ, required_env)
          ):
              if verbose:
                  utils.logger.info(
                      "Not using the DeepSpeed or dist launchers, attempting to detect MPI environment..."
                  )
              if in_aml() and not in_dlts():
                  patch_aml_env_for_torch_nccl_backend(verbose=verbose)
              elif in_aws_sm():
                  patch_aws_sm_env_for_torch_nccl_backend(
                      verbose=verbose
                  )
              else:
                  mpi_discovery(
                      distributed_port=distributed_port, verbose=verbose
                  )
  
          if cdb is not None and cdb.is_initialized():
              if int(os.getenv("RANK", "0")) == 0:
                  utils.logger.info(
                      "Distributed backend already initialized"
                  )
          else:
              assert isinstance(timeout, timedelta)
              if dist_backend is None:
                  dist_backend = (
                      get_accelerator().communication_backend_name()
                  )
              if int(os.getenv("RANK", "0")) == 0:
                  utils.logger.info(
                      "Initializing TorchBackend in DeepSpeed with backend {}".format(
                          dist_backend
                      )
                  )
              # Create a torch backend object, initialize torch distributed, and assign to cdb
              cdb = TorchBackend(
                  dist_backend, timeout, init_method, rank, world_size
              )
  
imports: import torch
  import os
  from ..constants import TORCH_DISTRIBUTED_DEFAULT_PORT, default_pg_timeout
  from .constants import *
  from .reduce_op import *
  from deepspeed.accelerator import get_accelerator
  from deepspeed.comm.ccl import CCLBackend
  from deepspeed.utils.comms_logging import CommsLogger
  from deepspeed.utils import timer, get_caller_func
  from deepspeed.comm.torch import TorchBackend
  from deepspeed import utils
  from datetime import timedelta
  from deepspeed.comm.utils import *
label_desc: Use image node_id 43 for calling a global function with example usage: init_distributed(dist_backend, auto_mpi_discovery, distributed_port, verbose, timeout, init_method, dist_init_required, config, rank, world_size) without return types