code: def __init__(
      self,
      num_steps,
      vocab,
      embedding_dim,
      rnn_units,
      rnn_type="bi_lstm",
      rnn_layers=1,
  ):
      self.num_steps = num_steps
      self.vocab = vocab
      self.embedding_dim = embedding_dim
  
      self.rnn_units = rnn_units
      self.rnn_type = rnn_type
      self.rnn_layers = rnn_layers
  
      # placeholder
      self.seq_len, self.input_seq = None, None
      # op
      self.encoder_output, self.encoder_state = None, None
  
imports: import tensorflow
  from tensorflow.contrib import rnn
  from tensorflow.python.ops import array_ops
  from ..models.basic_model import BasicModel
  import numpy
  import os
label_desc: Use image node_id 1 to create a new EncoderNet object  with example: obj = EncoderNet(num_steps, vocab, embedding_dim, rnn_units, rnn_type, rnn_layers)