code: def local_rank_and_size() -> Tuple[int, int]:
      # DeepSpeed CLI and other tools may set these environment variables for us.
      local_rank, local_size = os.environ.get(
          "LOCAL_RANK"
      ), os.environ.get("LOCAL_SIZE")
      if local_rank is not None and local_size is not None:
          return int(local_rank), int(local_size)
  
      # Gather the rank and hostnames from every worker so we can count up how many belong to the same host, which
      # constitutes the local group.
      rank = dist.get_rank()
      host = socket.gethostname()
      output = [None for _ in range(dist.get_world_size())]
      dist.all_gather_object(output, (rank, host))
  
      # Every time we find a worker with the same host, we increment the size counter.
      # The local rank is determined by the world rank relative to the other workers on the same host, so every time
      # we see a worker on our host with a lower rank, we increment the rank counter.
      local_size = 0
      local_rank = 0
      for other_rank, other_host in output:
          if other_host == host:
              local_size += 1
              if other_rank < rank:
                  local_rank += 1
  
      return local_rank, local_size
  
imports: import contextlib
  import logging
  import os
  import socket
  from typing import Any, Callable, Dict, Optional, Tuple, Type, TYPE_CHECKING, Union
  import torch
  import torch.distributed
  from ray.train.backend import BackendConfig
  from ray.train.data_parallel_trainer import DataParallelTrainer
  from ray.train.torch import TorchTrainer
  from torch import nn
  from torch.nn.parallel import DistributedDataParallel
  from torch.optim import Optimizer
  from torchmetrics.utilities.distributed import gather_all_tensors
  from ludwig.distributed.base import DistributedStrategy
  from ludwig.modules.optimization_modules import create_optimizer
  from ludwig.utils.torch_utils import get_torch_device
label_desc: Use image node_id 1 for calling a global function with example usage: local_rank_and_size() and returns: local_rank,  local_size, int,  int