class_docstr: Penn Treebank data set from http://arxiv.org/pdf/1409.2329v5.pdf
  
  Arguments:
      timesteps (int): number of timesteps to embed the data
      onehot_input (bool):
      tokenizer (str): name of the tokenizer function within this
                       class to use on the data
class_docstr_tok: ["Penn","Treebank","data","set","from","http",":","\/\/arxiv.org\/pdf\/1409.2329v5.pdf","Arguments",":","timesteps","(","int",")",":","number","of","timesteps","to","embed","the","data","onehot_input","(","bool",")",":","tokenizer","(","str",")",":","name","of","the","tokenizer","function","within","this","class","to","use","on","the","data"]
code: def load_data(self):
      self.file_paths = {}
      for phase in self.filemap:
          fn = self.gen_filename(phase)
          size = self.filemap[phase]
          self.file_paths[phase] = self.load_zip(fn, size)
      return self.file_paths
  
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 4 for calling the PTB obj's underlying member method code with example usage: obj.load_data() and returns: self