code: def __init__(
      self, dataset, num_replicas=None, rank=None, shuffle=True
  ):
      super().__init__(dataset, num_replicas=num_replicas, rank=rank)
      self.shuffle = shuffle
  
imports: import math
  import torch
  from torch.utils.data import DistributedSampler
label_desc: Use image node_id 1 to create a new DistributedSampler object from inherited base classes: _DistributedSampler with example: obj = DistributedSampler(dataset, num_replicas, rank, shuffle)