class_docstr: This class defines an iterator for loading and iterating the sentences in
  a structure to encode sentences into the skip-thought vectors
class_docstr_tok: ["This","class","defines","an","iterator","for","loading","and","iterating","the","sentences","in","a","structure","to","encode","sentences","into","the","skip-thought","vectors"]
docstr: For resetting 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: ["For","resetting","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):
      """
      For resetting 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
  
file_path: neon/examples/skip-thought/data_iterator.py
imports: from __future__ import division
  import numpy
  import h5py
  import copy
  from neon.data.dataiterator import NervanaDataIterator
label_desc: Use image node_id 2 for calling the SentenceEncode obj's underlying member method code with example usage: obj.reset() without return types