resnet.py 文件源码

def test(info):
    global net
    correct_sum = 0
    total_loss_sum = 0.
    total_ctr = 0
    for data in testloader:
        inputs, labels = data
        inputs, labels = Variable(inputs), Variable(labels)
        if global_cuda_available:
            inputs, labels = inputs.cuda(), labels.cuda()
        outputs = net(inputs)
        _, predicted = torch.max(outputs.data, 1)
        total_ctr += labels.size()[0]
        correct_sum += (predicted == labels.data).sum()
        loss = criterion(outputs, labels)
        total_loss_sum += loss.data[0]
    info[0] = correct_sum
    info[1] = total_ctr
    info[2] = total_loss_sum