Thank you！ you are really kind to reply me! Although i try use .cuda replace Variable and .to(device), it doesn`t work. But when I change my optimizer form SGD to Adam, the loss decrease ! And i am really really Happy!
But my most happy thing is you can reply me. It make me fell warm.
Last,Thank you! I finished it!
I know, maybe the learning_rate is to small, but it work on cpu…so strange.
my net(i run on jupyter):
class Net(nn.Module):
    def __init__(self):
        super(Net,self).__init__()
        self.conv1=nn.Conv2d(3,6,5)
        self.conv2=nn.Conv2d(6,16,5)
        self.fc1=nn.Linear(16*5*5,120)
        self.fc2=nn.Linear(120,84)
        self.fc3=nn.Linear(84,10)
    
    def forward(self,x):
        x=F.max_pool2d(F.relu(self.conv1(x)),(2,2))
        x=F.max_pool2d(F.relu(self.conv2(x)),2)
        x=x.view(x.size()[0],-1)
        x=F.relu(self.fc1(x))
        x=F.relu(self.fc2(x))
        x=self.fc3(x)
        return x
net=Net()

if t.cuda.is_available():
    net=net.cuda()

from torch import optim
criterion=nn.CrossEntropyLoss()
optimizer=optim.Adam(net.parameters(),lr=0.001)

for epoch in range(2):
    running_loss=0.0
    for i,data in enumerate(trainloader,0):
        inputs,labels=data
        if t.cuda.is_available():
            inputs=inputs.cuda()
            labels=labels.cuda()
        
        outputs=net(inputs)
        loss=criterion(outputs,labels)
        
        optimizer.zero_grad()
        loss.backward()
        optimizer.step()
        
        running_loss+=loss.item()
        if (i+1)%2000==1999:
            print('[%5d %5d] loss: %.3f'%(epoch+1,i+1,running_loss/2000))
            running_loss=0.0
print('Finished Training')

correct=0
total=0
for data in testloader:
    images,labels=data
    with t.no_grad():
        outputs=net(images.cuda()).cpu()
    _,predicted=t.max(outputs.data,1)
    total+=labels.size(0)
    correct+=(predicted==labels).sum()
print('test acc:%d %%'%(100*correct/total))

and results:
[    1  1999] loss: 1.874
[    1  3999] loss: 1.605
[    1  5999] loss: 1.514
[    1  7999] loss: 1.458
[    1  9999] loss: 1.422
[    1 11999] loss: 1.400
[    2  1999] loss: 1.316
[    2  3999] loss: 1.298
[    2  5999] loss: 1.280
[    2  7999] loss: 1.283
[    2  9999] loss: 1.274
[    2 11999] loss: 1.242
Finished Training

test acc:57 %