class_docstr: Representation of a set of tensor storages created by individual processes,
  allows to access those storages from a single owner process. The storages
  should either be shared or broadcasted to the owner process.
  The processes are identified by their rank, data is uniquely defined by
  the rank of the process and the record ID.
code: def get(self, rank: int, record_id: int) -> Dict[str, torch.Tensor]:
      storage = self.rank_to_storage[rank]
      return storage.get(record_id)
  
imports: import io
  import numpy
  import os
  from dataclasses import dataclass
  from functools import reduce
  from operator import mul
  from typing import BinaryIO, Dict, Optional, Tuple
  import torch
  from detectron2.utils.comm import gather, get_rank
  from detectron2.utils.file_io import PathManager
label_desc: Use image node_id 2 for calling the MultiProcessTensorStorage obj's underlying member method code with example usage: obj.get(rank, record_id) and returns: storage