【无标题】pytorch报错

报错TypeError: conv2d() received an invalid combination of arguments - got (tuple, Parameter, Parameter, tuple, tuple, tuple, int), but expected one of:

• (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, tuple of ints padding, tuple of ints dilation, int groups)
  didn’t match because some of the arguments have invalid types: (!tuple!, !Parameter!, !Parameter!, !tuple!, !tuple!, !tuple!, int)
• (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, str padding, tuple of ints dilation, int groups)
  didn’t match because some of the arguments have invalid types: (!tuple!, !Parameter!, !Parameter!, !tuple!, !tuple!, !tuple!, int)
  
  手写数字识别MNIST
  代码

def train(epoch_num):
    # 循环外可以自行添加必要内容
    running_loss = 0.0
    train_loss=[]
    #device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
    for index, data in enumerate(data_loader_train, 0):
        optimizer.zero_grad()
        #data = data.cpu().data.numpy()
        images, true_labels = data
        # 该部分添加训练的主要内容
        # 必要的时候可以添加损失函数值的信息，即训练到现在的平均损失或最后一次的损失，下面两行不必保留
        #print(images)
        
        #print(true_labels)
        optimizer.zero_grad()
        
        label = model(images)
        loss = loss_function(label,true_labels)
        running_loss += loss.item()
        
        
        loss.backward()
        
        optimizer.step()
        
        '''
        if(index%300 == 0):
            print('[%d, %5d] loss = %.3f' % (epoch_num + 1, index, running_loss / 300))
            running_loss = 0.0
        '''
        if index%100 == 99:
            print('[%d,%5d] loss :%.3f' %
                 (epoch+1,index+1,running_loss/100))
            running_loss = 0.0
        train_loss.append(loss.item())