networks.py 文件源码

def update(self, state, input, output=True):

        u_gate = tf.matmul(input, self.params['Uxh'])
        if state is not None:
            u_gate += tf.matmul(state, self.params['Uhh'])
            r_gate = tf.sigmoid(tf.matmul(input, self.params['Rxh']) + 
                                tf.matmul(state, self.params['Rhh']))
        u_gate = tf.sigmoid(u_gate)

        operand = tf.matmul(input, self.params['Wxh']) + self.params['bhid']
        if state is not None:
            operand += tf.matmul(state * r_gate, self.params['Whh'])
        new_state = self.coding(operand) * (1. - u_gate)
        if state is not None:
            new_state += state * u_gate

        if not output: return new_state
        return new_state, self.get_output(new_state)