code: def _initialize_default_inference_context(
      distributed_context: Optional[core.DistributedContext],
  ) -> core.Context:
      if distributed_context is None:
          distributed_context = _initialize_distributed_backend()
      # Use WorkerAskChief mode to ensure synchronize correctly across worker
      # Using WorkerAskMaster mode could lead to some workers exiting when others
      # are waiting for synchronization.
      return det.core.init(
          distributed=distributed_context,
          preempt_mode=core.PreemptMode.WorkersAskChief,
      )
  
imports: import abc
  import json
  import logging
  import math
  import os
  import pathlib
  import uuid
  import warnings
  from typing import TYPE_CHECKING, Any, ContextManager, Dict, Optional, Set, Sized, Type
  import torch
  import torch.distributed
  from torch import nn
  from torch.utils import data
  import determined
  from determined import common, core, pytorch
label_desc: Use image node_id 3 for calling a global function with example usage: _initialize_default_inference_context(distributed_context) and returns: det