class_docstr: A object which creates evaluation metrics for an Iteration.
class_docstr_tok: ["A","object","which","creates","evaluation","metrics","for","an","Iteration","."]
docstr: Returns best ensemble's metrics.
docstr_tok: ["Returns","best","ensemble","'s","metrics","."]
code: def best_eval_metric_ops(self, best_candidate_index, mode):
      """Returns best ensemble's metrics."""
  
      return _call_eval_metrics(
          self.best_eval_metrics_tuple(best_candidate_index, mode)
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import inspect
  from absl import logging
  from adanet import tf_compat
  import six
  import tensorflow.compat.v2
label_desc: Use image node_id 3 for calling the _IterationMetrics obj's underlying member method code with example usage: obj.best_eval_metric_ops(best_candidate_index, mode) and returns: _call_eval_metrics