class_docstr: A decoder for TensorFlow Examples.
  Decoding Example proto buffers is comprised of two stages: (1) Example parsing
  and (2) tensor manipulation.
  In the first stage, the tf.parse_example function is called with a list of
  FixedLenFeatures and SparseLenFeatures. These instances tell TF how to parse
  the example. The output of this stage is a set of tensors.
  In the second stage, the resulting tensors are manipulated to provide the
  requested 'item' tensors.
  To perform this decoding operation, an ExampleDecoder is given a list of
  ItemHandlers. Each ItemHandler indicates the set of features for stage 1 and
  contains the instructions for post_processing its tensors for stage 2.
docstr: See base class.
docstr_tok: ["See","base","class","."]
code: def list_items(self):
      """See base class."""
      return list(self._items_to_handlers.keys())
  
imports: import tensorflow
  from tensorflow.contrib.slim.python.slim.data import data_decoder
label_desc: Use image node_id 2 for calling the TFSEquenceExampleDecoder obj's underlying member method code with example usage: obj.list_items() and returns: list