class_docstr: This class defines methods for loading and iterating over text datasets.
class_docstr_tok: ["This","class","defines","methods","for","loading","and","iterating","over","text","datasets","."]
docstr: Reset the starting index of this dataset back to zero.
  Relevant for when one wants to call repeated evaluations on the dataset
  but don't want to wrap around for the last uneven minibatch
  Not necessary when ndata is divisible by batch size
docstr_tok: ["Reset","the","starting","index","of","this","dataset","back","to","zero",".","Relevant","for","when","one","wants","to","call","repeated","evaluations","on","the","dataset","but","do","n't","want","to","wrap","around","for","the","last","uneven","minibatch","Not","necessary","when","ndata","is","divisible","by","batch","size"]
code: def reset(self):
      """
      Reset the starting index of this dataset back to zero.
      Relevant for when one wants to call repeated evaluations on the dataset
      but don't want to wrap around for the last uneven minibatch
      Not necessary when ndata is divisible by batch size
      """
      self.batch_index = 0
  
imports: import logging
  import numpy
  import os
  import h5py
  from neon.data.dataiterator import NervanaDataIterator, ArrayIterator
  from neon.data.datasets import Dataset
  from neon.data.text_preprocessing import pad_sentences, pad_data
label_desc: Use image node_id 8 for calling the Text obj's underlying member method code with example usage: obj.reset() without return types