class_docstr: Random-state context manager class. Reference: https://github.com/luyug/GradCache.
  
  This class will back up the pytorch's random state during initialization. Then when the context is activated,
  the class will set up the random state with the backed-up one.
code: def __exit__(self, exc_type, exc_val, exc_tb):
      self._fork.__exit__(exc_type, exc_val, exc_tb)
      self._fork = None
  
imports: from __future__ import annotations
  from contextlib import nullcontext
  from functools import partial
  import torch
  from torch import nn, Tensor
  from torch.utils.checkpoint import get_device_states, set_device_states
  from typing import Iterable, Dict, Iterator, List, Optional, Tuple
  from sentence_transformers import SentenceTransformer
  from sentence_transformers import util
  import tqdm
label_desc: Use image node_id 3 for calling the RandContext obj's underlying member method code with example usage: obj.__exit__(exc_type, exc_val, exc_tb) without return types