PyTorch的 nn.CrossEntropyLoss()报错

nn.CrossEntropyLoss()
中两个参数，其中的标签必须为long型（int64）的，不能是float32

hwLabels = torch.Tensor(hwLabels).long()

loss_func = nn.CrossEntropyLoss() 
 for epoch in range(EPOCH):
        for step, (b_x, b_y) in enumerate(train_loader):  # gives batch data, normalize x when iterate train_loader
            output = cnn(b_x)[0]  # cnn output
            loss = loss_func(output, b_y)  # cross entropy loss
            optimizer.zero_grad()  # clear gradients for this training step
            loss.backward()  # backpropagation, compute gradients
            optimizer.step()  # apply gradients
            if step%5==0:
                loss_count.append(loss.detach().numpy())
                print('{}:\t'.format(step),"\tloss:",loss.item())
                #torch.save(cnn,r'save/model')