code: def __init__(self, vocab_size, hidden_size, init, keep):
      super(PTB_Net, self).__init__()
  
      self.embedding = tl.layers.Embedding(
          vocab_size, hidden_size, init
      )
      self.dropout1 = tl.layers.Dropout(keep=keep)
      self.lstm1 = tl.layers.RNN(
          cell=tf.keras.layers.LSTMCell(hidden_size),
          return_last_output=False,
          return_last_state=True,
          return_seq_2d=False,
          in_channels=hidden_size,
      )
      self.dropout2 = tl.layers.Dropout(keep=keep)
      self.lstm2 = tl.layers.RNN(
          cell=tf.keras.layers.LSTMCell(hidden_size),
          return_last_output=False,
          return_last_state=True,
          return_seq_2d=True,
          in_channels=hidden_size,
      )
      self.dropout3 = tl.layers.Dropout(keep=keep)
      self.out_dense = tl.layers.Dense(
          vocab_size,
          in_channels=hidden_size,
          W_init=init,
          b_init=init,
          act=None,
      )
  
file_path: TensorLayer/examples/text_ptb/tutorial_ptb_lstm.py
imports: import argparse
  import sys
  import time
  import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer.models import Model
label_desc: Use image node_id 1 to create a new PTB_Net object from inherited base classes: Model with example: obj = PTB_Net(vocab_size, hidden_size, init, keep)