class_docstr: Class for evaluation of minibatches against the specified evaluation function.
  
  Args:
     eval_function (:class:`~cntk.ops.functions.Function`): evaluation function.
     progress_writers (list): optionally, list of progress writers from :mod:`cntk.utils` to track
       training progress.
class_docstr_tok: ["Class","for","evaluation","of","minibatches","against","the","specified","evaluation","function",".","Args",":","eval_function","(",":","class",":","`","~cntk.ops.functions.Function","`",")",":","evaluation","function",".","progress_writers","(","list",")",":","optionally",",","list","of","progress","writers","from",":","mod",":","`","cntk.utils","`","to","track","training","progress","."]
docstr: The evaluation function that the evaluator is using.
docstr_tok: ["The","evaluation","function","that","the","evaluator","is","using","."]
code: def evaluation_function(self):
      """
      The evaluation function that the evaluator is using.
      """
      return super(Evaluator, self).evaluation_function()
  
file_path: CNTK/bindings/python/cntk/eval/evaluator.py
imports: from ..None import cntk_py
  from ..device import use_default_device
  from cntk.internal import sanitize_var_map, sanitize_function, typemap
  from ..io import MinibatchData
label_desc: Use image node_id 3 for calling the Evaluator obj's underlying member method code with example usage: obj.evaluation_function() and returns: super