import math
import matplotlib.pyplot as plt
import torch.optim as optim
from torchvision.models import resnet18
lr_rate = 0.0001
model = resnet18(num_classes=10)
# T_max = 1000
epoch_total = 25
epoch_iter = 609
warm_up = 800
lambda1 = lambda epoch: (epoch / warm_up) if epoch < warm_up else 0.5 * (math.cos((epoch - warm_up)/(epoch_total*epoch_iter - warm_up) * math.pi) + 1)
optimizer = optim.SGD(model.parameters(), lr=lr_rate, momentum=0.9, nesterov=True)
scheduler = optim.lr_scheduler.LambdaLR(optimizer, lr_lambda=lambda1)
index = 0
x = []
y = []
for epoch in range(epoch_total):
for batch in range(609):
x.appe发布者：admin，转转请注明出处：http://www.yc00.com/web/1754914643a5214881.html
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