import tensorflow as tf

        self.saver = tf.train.Saver()
        
        
    def train_network(self):
        
        self.learning_rate = tf.placeholder(tf.float32)
        self.d_optimizer = tf.train.AdamOptimizer(self.learning_rate,beta1=self.beta1,beta2=self.beta2).minimize(self.discriminator_loss,var_list=self.d_variables)
        self.g_optimizer = tf.train.AdamOptimizer(self.learning_rate,beta1=self.beta1,beta2=self.beta2).minimize(self.generator_loss,var_list=self.g_variables)      
        
        self.init_op = tf.global_variables_initializer()
        self.sess = tf.Session()
        self.sess.run(self.init_op)
