class_docstr: Vacuous indexer to be used with final layers.
  
  FullIndex is a compatibility class to be used with meta layers. It stores
  the sample size to be predicted for use with the
  :class:`ParallelProcessing` job manager, and yields a ``None, None``
  index when `generate` is called.
class_docstr_tok: ["Vacuous","indexer","to","be","used","with","final","layers",".","FullIndex","is","a","compatibility","class","to","be","used","with","meta","layers",".","It","stores","the","sample","size","to","be","predicted","for","use","with","the",":","class",":","`","ParallelProcessing","`","job","manager",",","and","yields","a","``","None",",","None","``","index","when","`","generate","`","is","called","."]
docstr: Vacuous generator to ensure training data is not sliced.
docstr_tok: ["Vacuous","generator","to","ensure","training","data","is","not","sliced","."]
code: def _gen_indices(self):
      """Vacuous generator to ensure training data is not sliced."""
      yield None, None
  
imports: from __future__ import division
  from abc import abstractmethod
  import numpy
  from ..externals.sklearn.base import BaseEstimator
label_desc: Use image node_id 3 for calling the FullIndex obj's underlying member method code with example usage: obj._gen_indices() without return types