optim.py 文件源码

def decay_learning_rate(opt, factor, final_value):
    if isinstance(opt, optimizers.NesterovAG):
        if opt.lr <= final_value:
            return final_value
        opt.lr *= factor
        return
    if isinstance(opt, optimizers.SGD):
        if opt.lr <= final_value:
            return final_value
        opt.lr *= factor
        return
    if isinstance(opt, optimizers.MomentumSGD):
        if opt.lr <= final_value:
            return final_value
        opt.lr *= factor
        return
    if isinstance(opt, optimizers.Adam):
        if opt.alpha <= final_value:
            return final_value
        opt.alpha *= factor
        return
    raise NotImplementedError()