Hands-On Deep Learning Algorithms with Python

Defining the weights

First, let's define all the weights. The weights of the update gate are defined as follows:

 Uz = tf.get_variable("Uz", [vocab_size, hidden_size], initializer=init) Wz = tf.get_variable("Wz", [hidden_size, hidden_size], initializer=init) bz = tf.get_variable("bz", [hidden_size], initializer=init)

The weights of the reset gate are defined as shown:

Ur = tf.get_variable("Ur", [vocab_size, hidden_size], initializer=init)Wr = tf.get_variable("Wr", [hidden_size, hidden_size], initializer=init)br = tf.get_variable("br", [hidden_size], initializer=init)

The weights of the content state are defined as follows:

Uc = tf.get_variable("Uc", [vocab_size, hidden_size], initializer=init)Wc = tf.get_variable("Wc", [hidden_size, hidden_size], ...