yeah after some research, I saw that it is cwh problem. currently I am trying to find the solution to reverse the order.
My code is like this:
    datasetTrain=FencerPicLoader('D:/x/x/x',transformations)
    train_loader=DataLoader(dataset=datasetTrain,
                            batch_size=5,  
                            shuffle=True,   
                            num_workers=2) 

    for epoch in range(2):  # loop over the dataset multiple times

        running_loss = 0.0
        for i, data in enumerate(train_loader, 0):
            # get the inputs
            inputs, labels = data

            # zero the parameter gradients
            optimizer.zero_grad()

            # forward + backward + optimize
            outputs = net(inputs)#####error jumps to Net()




class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(3, 5, 436) 
        self.pool = nn.MaxPool2d(2, 2)
        self.conv2 = nn.Conv2d(6, 16, 5) 
        self.fc1 = nn.Linear(16 * 5 * 5, 120)
        self.fc2 = nn.Linear(120, 84)
        self.fc3 = nn.Linear(84, 10)

Thanks for help and kernel advice!