test 测试网络模板

from torch.autograd import Variable
import  torch.nn.functional as F

def test(model,test_loader,device):
    model.eval()  # 设置为test模式
    test_loss = 0  # 初始化测试损失值为0
    correct = 0  # 初始化预测正确的数据个数为0
    for data, target in test_loader:
        data = data.to(device)
        target = target.to(device)
        data, target = Variable(data), Variable(target)  # 计算前要把变量变成Variable形式，因为这样子才有梯度

        output = model(data)
        test_loss += F.cross_entropy(output, target, size_average=False).item()  # sum up batch loss 把所有loss值进行累加
        pred = output.data.max(1, keepdim=True)[1]  # get the index of the max log-probability
        correct += pred.eq(target.data.view_as(pred)).cpu().sum()  # 对预测正确的数据个数进行累加

    test_loss /= len(test_loader.dataset)