Python PyTorch SequentialLR用法及代码示例

本文简要介绍python语言中 torch.optim.lr_scheduler.SequentialLR 的用法。

用法:

class torch.optim.lr_scheduler.SequentialLR(optimizer, schedulers, milestones, last_epoch=- 1, verbose=False)

参数：

• schedulers(list) -链式调度程序列表。

• milestones(list) -反映里程碑点的整数列表。

接收预计在优化过程中按顺序调用的调度程序列表和提供准确间隔以反映在给定时期应该调用哪个调度程序的里程碑点。

示例

>>> # Assuming optimizer uses lr = 1. for all groups
>>> # lr = 0.1     if epoch == 0
>>> # lr = 0.1     if epoch == 1
>>> # lr = 0.9     if epoch == 2
>>> # lr = 0.81    if epoch == 3
>>> # lr = 0.729   if epoch == 4
>>> scheduler1 = ConstantLR(self.opt, factor=0.1, total_iters=2)
>>> scheduler2 = ExponentialLR(self.opt, gamma=0.9)
>>> scheduler = SequentialLR(self.opt, schedulers=[scheduler1, scheduler2], milestones=[2])
>>> for epoch in range(100):
>>>     train(...)
>>>     validate(...)
>>>     scheduler.step()