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: Store dimensionality data about X.
docstr_tok: ["Store","dimensionality","data","about","X","."]
code: def fit(self, X, y=None, job=None):
      """Store dimensionality data about X."""
      self.n_samples = X.shape[0]
      self.n_test_samples = X.shape[0]
      self.__fitted__ = True
  
imports: from __future__ import division
  from abc import abstractmethod
  import numpy
  from ..externals.sklearn.base import BaseEstimator
label_desc: Use image node_id 2 for calling the FullIndex obj's underlying member method code with example usage: obj.fit(X, y, job) without return types