class_docstr: A object which creates evaluation metrics for Ensembles.
class_docstr_tok: ["A","object","which","creates","evaluation","metrics","for","Ensembles","."]
docstr: Overrides parent's method to also add the ensemble's architecture.
docstr_tok: ["Overrides","parent","'s","method","to","also","add","the","ensemble","'s","architecture","."]
code: def create_eval_metrics(
      self, features, labels, estimator_spec, metric_fn, architecture
  ):
      """Overrides parent's method to also add the ensemble's architecture."""
  
      super(_EnsembleMetrics, self).create_eval_metrics(
          features, labels, estimator_spec, metric_fn
      )
      self._eval_metrics_store.add_eval_metrics(
          self._architecture_as_metric(architecture), []
      )
  
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 1 for calling the _EnsembleMetrics obj's underlying member method code with example usage: obj.create_eval_metrics(features, labels, estimator_spec, metric_fn, architecture) without return types