class_docstr: A hierarchical encoder that stacks basic RNN encoders into two layers.
  Can be used to encode long, structured sequences, e.g. paragraphs, dialog
  history, etc.
  
  Args:
      encoder_major (optional): An instance of subclass of
          :class:`~texar.tf.modules.RNNEncoderBase`
          The high-level encoder taking final
          states from low-level encoder as its
          inputs. If not specified, an encoder
          is created as specified in
          :attr:`hparams["encoder_major"]`.
      encoder_minor (optional): An instance of subclass of
          :class:`~texar.tf.modules.RNNEncoderBase`
          The low-level encoder. If not
          specified, an encoder is created as specified
          in :attr:`hparams["encoder_minor"]`.
      hparams (dict or HParams, optional): Hyperparameters. Missing
          hyperparamerter will be set to default values. See
          :meth:`default_hparams` for the hyperparameter sturcture and
          default values.
  
  See :meth:`_build` for the inputs and outputs of the encoder.
  
  .. document private functions
  .. automethod:: _build
docstr: The low-level encoder.
          
docstr_tok: ["The","low-level","encoder","."]
code: def encoder_minor(self):
      """The low-level encoder."""
      return self._encoder_minor
  
file_path: texar/texar/tf/modules/encoders/hierarchical_encoders.py
imports: import collections
  import tensorflow
  from tensorflow.contrib.rnn import LSTMStateTuple
  from tensorflow.python.util import nest
  from texar.tf.modules.encoders.encoder_base import EncoderBase
  from texar.tf.utils import utils
label_desc: Use image node_id 8 for calling the HierarchicalRNNEncoder obj's underlying member method code with example usage: obj.encoder_minor() and returns: self