Thanks for reply @ptrblck. I applied as you said, but probably i’ve a problem into test phase. For a better understanding a put the code:
with torch.no_grad():
    for data, labels in testloader:
        if use_gpu:
            data, labels = data.cuda(), labels.cuda()

        features = model(data)
        sm = torch.nn.Softmax()
        probabilities = sm(features)

        predictions = probabilities.data.max(1)[1]
        total += labels.size(0)
        correct += (predictions == labels.data).sum()

Is it correct to pass the layer of Softmax result to get accuracy? This is my first time I use VGG19. Thanks for your help.