class_docstr: Base class for all RNN encoder classes to inherit.
  
  Args:
      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.
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docstr: Encodes the inputs.
  
  Args:
      inputs: Inputs to the encoder.
      *args: Other arguments.
      **kwargs: Keyword arguments.
  
  Returns:
      Encoding results.
docstr_tok: ["Encodes","the","inputs",".","Args",":","inputs",":","Inputs","to","the","encoder",".","*","args",":","Other","arguments",".","*","*","kwargs",":","Keyword","arguments",".","Returns",":","Encoding","results","."]
code: def _build(self, inputs, *args, **kwargs):
      """Encodes the inputs.
  
      Args:
          inputs: Inputs to the encoder.
          *args: Other arguments.
          **kwargs: Keyword arguments.
  
      Returns:
          Encoding results.
      """
      raise NotImplementedError
  
imports: import functools
  import numpy
  import tensorflow
  from tensorflow.contrib.framework import nest
  from texar.tf.modules.encoders.encoder_base import EncoderBase
  from texar.tf.modules.networks.conv_networks import _to_list
  from texar.tf.core import layers
  from texar.tf.utils.mode import is_train_mode
  from texar.tf.utils.shapes import mask_sequences
  from texar.tf.hyperparams import HParams
label_desc: Use image node_id 3 for calling the RNNEncoderBase obj's underlying member method code with example usage: obj._build(inputs) without return types