class_docstr: A sequential sampler used in FeatureSet when get (train=false) iterator .
code: def __iter__(self):
      indices = list(range(self.offset, self.num_samples + self.offset))
  
      assert len(indices) == self.num_samples
  
      return iter(indices)
  
file_path: analytics-zoo/pyzoo/zoo/pipeline/api/torch/utils.py
imports: from torch.utils.data.sampler import Sampler
  import math
label_desc: Use image node_id 2 for calling the DistributedSequentialSampler obj's underlying member method code with example usage: obj.__iter__() and returns: iter