code: def __init__(
      self,
      decision_num,
      out_dims,
      embedding_dim,
      cell_type="lstm",
      rnn_layers=1,
      attention_config=None,
  ):
      self.decision_num = decision_num
      self.out_dims = out_dims
      self.embedding_dim = embedding_dim
  
      self.cell_type = cell_type
      self.rnn_layers = rnn_layers
      self.attention_config = attention_config
  
      # placeholder
      self.block_layer_num = None
      # op
      self.decision, self.probs = 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 DeeperActorNet object  with example: obj = DeeperActorNet(decision_num, out_dims, embedding_dim, cell_type, rnn_layers, attention_config)