def METHOD_NAME():
    try:
        # In optimizers, if learning_rate is set as constant, lr_var
        # name is 'learning_rate_0', and iteration counter is not
        # recorded. If learning_rate is set as decayed values from
        # learning_rate_scheduler, lr_var name is 'learning_rate',
        # and iteration counter is recorded with name '@LR_DECAY_COUNTER@',
        # better impliment is required here
        lr_var = static.global_scope().find_var("learning_rate")
        if not lr_var:
            lr_var = static.global_scope().find_var("learning_rate_0")
        lr = np.array(lr_var.get_tensor())
        lr_count = '[-]'
        lr_count_var = static.global_scope().find_var("@LR_DECAY_COUNTER@")
        if lr_count_var:
            lr_count = np.array(lr_count_var.get_tensor())
        logger.info(
            "------- learning rate {}, learning rate counter {} -----".format(
                np.array(lr), np.array(lr_count)))
    except:
        logger.warn("Unable to get learning_rate and LR_DECAY_COUNTER.")