class_docstr: Samples elements randomly over multiple epochs
  
  Arguments:
      data_source (Dataset): dataset to sample from
      num_iter (int) : Number of times to loop over the dataset
      start_itr (int) : which iteration to begin from
code: def __len__(self):
      return (self.num_iter - self.start_itr) * self.batch_size
  
imports: import numpy
  import torch.utils.data
label_desc: Use image node_id 3 for calling the MultiEpochSampler obj's underlying member method code with example usage: obj.__len__() and returns: unknown