code: def reduce_dict_sum(input_dict: Dict[Any, Any]) -> Dict[Any, Any]:
      """
      Reduce the values in the dictionary from all processes so that all processes
      have the sum of the all values. Returns a dict with the same fields as
      input_dict, after reduction.
  
      Note: This function can work on defaultdict(list) and will effectively
      concatenate multiple dictionaries into single one, thanks to that summation
      of lists works as a concatenation.
      Args:
          input_dict (dict): all the values will be reduced
      """
      world_size = get_world_size()
      if world_size < 2:
          return input_dict
  
      with torch.no_grad():
          reduced_dict = {}
          for x in all_gather(input_dict):
              for key, value in x.items():
                  if key in reduced_dict:
                      reduced_dict[key] += value
                  else:
                      reduced_dict[key] = value
      return reduced_dict
  
imports: import gc
  import inspect
  import logging
  import os
  import pickle
  import typing
  import functools
  from typing import Any, Dict, List, Optional
  import numpy
  import torch
  from torch import Tensor
  import torch.distributed
  from pytorch_toolbelt.utils.bucket_assignment import naive_bucket_assignment, compute_bucket_imbalance_score, random_bucket_assignment, filler_bucket_assignment
label_desc: Use image node_id 8 for calling a global function with example usage: reduce_dict_sum(input_dict) and returns: reduced_dict, input_dict