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","."]
code: def __init__(self, X=None):
      super(FullIndex, self).__init__()
      if X is not None:
          self.fit(X)
  
imports: from __future__ import division
  from abc import abstractmethod
  import numpy
  from ..externals.sklearn.base import BaseEstimator
label_desc: Use image node_id 1 to create a new FullIndex object from inherited base classes: BaseIndex with example: obj = FullIndex(X)