class_docstr: Abstraction for using a EvalSavedModel.
  
  Note that this class overrides eval_metrics_graph.EvalMetricsGraph
  which contains most of the functionality for handling the metric ops.
  In the eval saved model path, a common graph is shared between generation
  FeaturesPredictionLabels through Predict and doing the metric ops.
  The specific methods of this class constructs the graph and handles
  the prediction ops.
docstr: Iterate through features, predictions, labels maps in canonical order.
  
  We need to fix a canonical order because to use `make_callable`, we must use
  a list for feeding Tensor values. This means we need to generate the
  values to feed in the same order that we generated the list of parameters
  for `make_callable`.
  
  Each of features_map, predictions_map, and labels_map are OrderedDicts,
  so the iteration order is stable.
  
  The map names returned are chosen to correspond to the fields of
  FeaturesPredictionsLabels, so callers can do getattr(fpl, map_name) to
  get the corresponding field.
  
  Yields:
    Tuples of (map name, map key, map value)
docstr_tok: ["Iterate","through","features",",","predictions",",","labels","maps","in","canonical","order",".","We","need","to","fix","a","canonical","order","because","to","use","`","make_callable","`",",","we","must","use","a","list","for","feeding","Tensor","values",".","This","means","we","need","to","generate","the","values","to","feed","in","the","same","order","that","we","generated","the","list","of","parameters","for","`","make_callable","`",".","Each","of","features_map",",","predictions_map",",","and","labels_map","are","OrderedDicts",",","so","the","iteration","order","is","stable",".","The","map","names","returned","are","chosen","to","correspond","to","the","fields","of","FeaturesPredictionsLabels",",","so","callers","can","do","getattr","(","fpl",",","map_name",")","to","get","the","corresponding","field",".","Yields",":","Tuples","of","(","map","name",",","map","key",",","map","value",")"]
code: def _iterate_fpl_maps_in_canonical_order(
      self,
  ) -> Generator[
      Tuple[str, types.FPLKeyType, types.TensorType], None, None
  ]:
      """Iterate through features, predictions, labels maps in canonical order.
  
      We need to fix a canonical order because to use `make_callable`, we must use
      a list for feeding Tensor values. This means we need to generate the
      values to feed in the same order that we generated the list of parameters
      for `make_callable`.
  
      Each of features_map, predictions_map, and labels_map are OrderedDicts,
      so the iteration order is stable.
  
      The map names returned are chosen to correspond to the fields of
      FeaturesPredictionsLabels, so callers can do getattr(fpl, map_name) to
      get the corresponding field.
  
      Yields:
        Tuples of (map name, map key, map value)
      """
      for feature_key, feature_value in self._features_map.items():
          yield "features", feature_key, feature_value  # pytype: disable=bad-return-type
      for (
          prediction_key,
          prediction_value,
      ) in self._predictions_map.items():
          yield "predictions", prediction_key, prediction_value  # pytype: disable=bad-return-type
      for label_key, label_value in self._labels_map.items():
          yield "labels", label_key, label_value
  
imports: from typing import Any, Dict, Generator, List, NamedTuple, Optional, Tuple, Union
  import numpy
  import tensorflow
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.eval_metrics_graph import eval_metrics_graph
  from tensorflow_model_analysis.eval_saved_model import constants
  from tensorflow_model_analysis.eval_saved_model import encoding
  from tensorflow_model_analysis.eval_saved_model import graph_ref
  from tensorflow_model_analysis.eval_saved_model import util
  from tensorflow.core.protobuf import meta_graph_pb2
label_desc: Use image node_id 5 for calling the EvalSavedModel obj's underlying member method code with example usage: obj._iterate_fpl_maps_in_canonical_order() without return types