class_docstr: An abstract ensemble of subnetworks.
class_docstr_tok: ["An","abstract","ensemble","of","subnetworks","."]
docstr: Optional dict of Ensemble predictions to be merged in EstimatorSpec.
  
  These will be additional (over the default included by the head) predictions
  which will be included in the EstimatorSpec in `predictions` and
  `export_outputs` (wrapped as PredictOutput).
docstr_tok: ["Optional","dict","of","Ensemble","predictions","to","be","merged","in","EstimatorSpec",".","These","will","be","additional","(","over","the","default","included","by","the","head",")","predictions","which","will","be","included","in","the","EstimatorSpec","in","`","predictions","`","and","`","export_outputs","`","(","wrapped","as","PredictOutput",")","."]
code: def predictions(self):
      """Optional dict of Ensemble predictions to be merged in EstimatorSpec.
  
      These will be additional (over the default included by the head) predictions
      which will be included in the EstimatorSpec in `predictions` and
      `export_outputs` (wrapped as PredictOutput).
      """
      return None
  
file_path: adanet/adanet/ensemble/ensembler.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import collections
  import six
label_desc: Use image node_id 3 for calling the Ensemble obj's underlying member method code with example usage: obj.predictions() and returns: None