code: def decode_example(self, serialized_example):
      
      data_fields, data_items_to_decoders = self.example_reading_spec()
      # Necessary to rejoin examples in the correct order with the Cloud ML Engine
      # batch prediction API.
      data_fields["batch_prediction_key"] = tf.FixedLenFeature([1], tf.int64, 0)
      if data_items_to_decoders is None:
        data_items_to_decoders = {
            field: tf.contrib.slim.tfexample_decoder.Tensor(field)
            for field in data_fields
        }
  
      decoder = tf.contrib.slim.tfexample_decoder.TFExampleDecoder(
          data_fields, data_items_to_decoders)
  
      decode_items = list(sorted(data_items_to_decoders))
      decoded = decoder.decode(serialized_example, items=decode_items)
      return dict(zip(decode_items, decoded))
docs: Return a dict of Tensors from a serialized tensorflow.Example.