model.py 文件源码

def linear_schedule(self, schedules, rate):
        schedules = np.array([-1]+schedules) * self.parameters['full_epoch']
        ratios = np.ones_like(schedules)
        print(schedules,ratios)
        for i in range(len(ratios)):
            ratios[i] = self.parameters['lr'] * (rate**i)
        def fn(epoch):
            for i,s in enumerate(schedules):
                if epoch < s:
                    return float(ratios[i-1])
            return float(ratios[-1])
        return LearningRateScheduler(fn)