class_docstr: A Kinesis Dataset that consumes the message.
  
  Kinesis is a managed service provided by AWS for data streaming.
  This dataset reads messages from Kinesis with each message presented
  as a `tf.string`.
  
  For example, we can construct and use the KinesisIODataset as follows:
  ```python
  dataset = KinesisIODataset(
      "kinesis_stream_name", read_indefinitely=False)
  next = dataset.make_one_shot_iterator().get_next()
  with tf.Session() as sess:
    while True:
      try:
        print(sess.run(nxt))
      except tf.errors.OutOfRangeError:
        break
  ```
  
  Since Kinesis is a data streaming service, data may not be available
  at the time it is being read. The argument `read_indefinitely` is
  used to control the behavior in this situation. If `read_indefinitely`
  is `True`, then `KinesisIODataset` will keep retrying to retrieve data
  from the stream. If `read_indefinitely` is `False`, an `OutOfRangeError`
  is returned immediately instead.
code: def _inputs(self):
      return []
  
imports: import tensorflow
  from tensorflow_io.python.ops import core_ops
label_desc: Use image node_id 2 for calling the KinesisIODataset obj's underlying member method code with example usage: obj._inputs() and returns: list