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: Returns fetches (features, predictions, labels, etc) for single_input.
  
  Args:
    single_input: Data to use to feed the input tensors. This must align with
      the receiver_tensors passed to EvalInputReceiver. For example, if
      receiver_tensors was a placeholder for parsing `tf.train.Example`
      protos, then this will be a serialised `tf.train.Example`.
  
  Returns:
    A list of FetchedTensorValues (one per example used by model). In most
    cases a single input will result in one example and the returned list will
    contain only one element, but in some cases (e.g. where examples are
    dynamically decoded and generated within the graph), the single input
    might result in zero to many examples).
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code: def predict(
      self, single_input: SingleInputFeedType
  ) -> List[FetchedTensorValues]:
      """Returns fetches (features, predictions, labels, etc) for single_input.
  
      Args:
        single_input: Data to use to feed the input tensors. This must align with
          the receiver_tensors passed to EvalInputReceiver. For example, if
          receiver_tensors was a placeholder for parsing `tf.train.Example`
          protos, then this will be a serialised `tf.train.Example`.
  
      Returns:
        A list of FetchedTensorValues (one per example used by model). In most
        cases a single input will result in one example and the returned list will
        contain only one element, but in some cases (e.g. where examples are
        dynamically decoded and generated within the graph), the single input
        might result in zero to many examples).
      """
      return self.predict_list([single_input])
  
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 9 for calling the EvalSavedModel obj's underlying member method code with example usage: obj.predict(single_input) and returns: self