example6_gradient.py 文件源码

def train(epoch):
    model.train()
    for batch_idx, (data, target) in enumerate(train_loader):
        data, target = Variable(data, requires_grad=True), Variable(target)
        optimizer.zero_grad()
        output = model(data)
        loss = F.cross_entropy(output, target)
        loss.backward()
        optimizer.step()

        # Display the gradients
        plt.clf()
        plt.subplot(211); plt.hist(forward_grad.ravel()); plt.title("Features magnitude")
        plt.subplot(212); plt.hist(backward_grad.ravel()); plt.title("Gradients")
        plt.show(block=False)
        plt.pause(0.01)

        print('Train Epoch: {} [{}/{} ({:.0f}%)]\tLoss: {:.6f}'.format(
            epoch, batch_idx * len(data), len(train_loader.dataset),
            100. * batch_idx / len(train_loader), loss.data[0]))