optimizer=torch.optim.Adam(net.parameters(),lr=0.01) #学习率为0.01的学习器

scheduler=torch.optim.lr_scheduler.StepLR(optimizer,step_size=30,gamma=0.9) #每过30个epoch训练，学习率就乘gamma

for epoch in range(100):
for step, (x, y) in enumerate(train_loader):
train(…)
optimizer.step()

scheduler.step()

scheduler=torch.optim.lr_scheduler.ReduceLROnPlateau(optimizer,mode=‘min’,factor=0.9) #mode为min，则loss不下降学习率乘以factor，max则反之

for epoch in range(100):

for step, (x, y) in enumerate(train_loader):

train(…)

optimizer.step()

scheduler.step(loss)