class_docstr: A stacked bidirectional RNN encoder. Uses the same cell for both the
  forward and backward RNN. Stacking should be performed as part of
  the cell.
  
  Args:
    cell: An instance of tf.contrib.rnn.RNNCell
    name: A name for the encoder
class_docstr_tok: ["A","stacked","bidirectional","RNN","encoder",".","Uses","the","same","cell","for","both","the","forward","and","backward","RNN",".","Stacking","should","be","performed","as","part","of","the","cell",".","Args",":","cell",":","An","instance","of","tf.contrib.rnn.RNNCell","name",":","A","name","for","the","encoder"]
code: def default_params():
      return {
          "rnn_cell": _default_rnn_cell_params(),
          "init_scale": 0.04,
      }
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import tensorflow
  from tensorflow.contrib.rnn.python.ops import rnn
  from seq2seq.encoders.encoder import Encoder, EncoderOutput
  from seq2seq.training import utils
label_desc: Use image node_id 2 for calling the StackBidirectionalRNNEncoder obj's underlying member method code with example usage: obj.default_params() and returns: dict