docstr: Subsample a small set of samplers from all class-samplers
docstr_tok: ["Subsample","a","small","set","of","samplers","from","all","class-samplers"]
code: def _subsample_samplers(self, samplers):
      """Subsample a small set of samplers from all class-samplers"""
      subsample = self._get_perm_ssi()
      subsampled_samplers = []
      for i in subsample:
          subsampled_samplers.append(samplers[i])
      self._next_ssi()
      return zip(*subsampled_samplers)
  
imports: import contextlib
  import logging
  import queue
  from typing import Dict, List
  import numpy
  import torch
  from PIL import Image
  from torch.utils.data import Dataset
  from torch.utils.data.distributed import DistributedSampler
label_desc: Use image node_id 9 for calling the StratifiedClassSampler obj's underlying member method code with example usage: obj._subsample_samplers(samplers) and returns: zip