learning rate schedule is exponential decay: lr = conf.learning_rate*(conf.gamma**(float(cur_step)/conf.decay_steps))</p>

        <p>Override this function to implement a different training function. If you override this, you need to override the get_pred_fn as well. For saving the models, call self.create_saver() after creating the network but before creating a session to setup the saver. Call self.save(sess, step_no)  every self.conf.save_step to save intermediate models. At the end of training, again ca