Pytorch - Typeerror: 'Torch. Size' Object Cannot Be Interpreted as an Integer

Hi I am training a PyTorch model and occurred this error:

----> 5 for i, data in enumerate(trainloader, 0):

TypeError: 'torch.Size' object cannot be interpreted as an integer

Not sure what this error means.

You can find my code here :

model.train()
for epoch in range(10):
    running_loss = 0

    for i, data in enumerate(trainloader, 0):

        inputs, labels = data

        optimizer.zero_grad()

        outputs = model(inputs)
        loss = criterion(outputs, labels)
        loss.backward()
        optimizer.step()

        if i % 2000 == 0:
          print (loss.item())
        running_loss += loss.item()
        if i % 1000 == 0:
            print ('[%d, %5d] loss: %.3f' % (epoch, i, running_loss/ 1000))
            running_loss = 0

torch.save(model, 'FeatureNet.pkl')

Update

This is the codeblock for DataLoader. I am using a customized dataloader and datasets, which x are pictures with size (1025, 16) and y are one-hot encoded vectors for classification.

x_train.shape = (1100, 1025, 16)

y_train.shape = (1100, 10)

clean_dir = '/home/tk/Documents/clean/' 
mix_dir = '/home/tk/Documents/mix/' 
clean_label_dir = '/home/tk/Documents/clean_labels/' 
mix_label_dir = '/home/tk/Documents/mix_labels/' 

class MSourceDataSet(Dataset):

    def __init__(self, clean_dir, mix_dir, clean_label_dir, mix_label_dir):

        with open(clean_dir + 'clean0.json') as f:
            clean0 = torch.Tensor(json.load(f))

        with open(mix_dir + 'mix0.json') as f:
            mix0 = torch.Tensor(json.load(f))

        with open(clean_label_dir + 'clean_label0.json') as f:
            clean_label0 = torch.Tensor(json.load(f))


        with open(mix_label_dir + 'mix_label0.json') as f:
            mix_label0 = torch.Tensor(json.load(f))


        self.spec = torch.cat([clean0, mix0], 0)
        self.label = torch.cat([clean_label0, mix_label0], 0)

    def __len__(self):
        return self.spec.shape


    def __getitem__(self, index): 

        spec = self.spec[index]
        label = self.label[index]
        return spec, label

getitem

a, b = trainset.__getitem__(1000)
print (a.shape)
print (b.shape)

a.shape = torch.Size([1025, 16]); b.shape = torch.Size([10])