my code couldn't find instance that was created initialized using pytorch

Question

I implemented dataset class to use model, and When i strated train i get error

Traceback (most recent call last):
  File "model.py", line 146, in <module>
    train = Train()
  File "model.py", line 70, in __init__
    self.dataset.get_label()
  File "model.py", line 61, in get_label
    return self.label
AttributeError: 'MaskDataset' object has no attribute 'label'

and bellow code is maked error. but I never know why it's make problem. I check 'self.imgs' and 'self.label' used print(self.imgs) and print(self.label). and it was perfecte.

So I Mean, I don't know why python interpreter couldn't find instance that created initialized.

class MaskDataset(object):
def __init__(self, transforms,path):
    self.data = data.Data()
    self.transform = transforms
    self.path = path

    if 'Validation' in self.path :
        self.img_path = "/home/ubuntu/lecttue-diagonosis/YangDongJae/ai/data/Validation/images/"
        self.lab_path = "/home/ubuntu/lecttue-diagonosis/YangDongJae/ai/data/Validation/annotations/"
        self.label = list(sorted(os.listdir(self.lab_path)))
        self.imgs = list(sorted(os.listdir(self.img_path)))

    elif 'train' in self.path:
        self.img_path = "/home/ubuntu/lecttue-diagonosis/YangDongJae/ai/data/Training/images/"
        self.lab_path = "/home/ubuntu/lecttue-diagonosis/YangDongJae/ai/data/Training/annotations/"
        self.label = list(sorted(os.listdir(self.lab_path)))
        self.imgs = list(sorted(os.listdir(self.img_path)))

    def __getitem__(self,idx):
        file_image = self.imgs[idx]
        file_label = self.label[idx]
        img_path = self.img_path+file_image
        label_path = self.lab_path + file_label

        img = Image.open(img_path).convert("RGB")
        target = self.data.generate_target(label_path)

        if self.transform is not None:
            img = self.transform(img)

        return img, target

class Train(MaskDataset):
    def __init__(self,epochs = 100, lr = 0.005, momentum = 0.9, weight_decay = 0.0005):
        self.data_transform = transforms.Compose([  # transforms.Compose : list 내의 작업을 연달아 할 수 있게 호출하는 클래스
                transforms.ToTensor() # ToTensor : numpy 이미지에서 torch 이미지로 변경
            ])

        self.dataset = MaskDataset(self.data_transform,'/home/ubuntu/lecttue-diagonosis/YangDongJae/ai/data/Training/')
        self.val_dataset = MaskDataset(self.data_transform, '/home/ubuntu/lecttue-diagonosis/YangDongJae/ai/data/Validation/')
        self.data_loader = torch.utils.data.DataLoader(self.dataset, batch_size = 10, collate_fn = self.collate_fn)
        self.val_data_loader = torch.utils.data.DataLoader(self.val_dataset, batch_size = 10,collate_fn = self.collate_fn)
        self.num_classes = 8
        self.epochs = epochs
        self.momentum = momentum
        self.lr = 0.005
        self.weight_decay = weight_decay

Answer 1

This is happening because elif condition is not True during self.dataset object creation. Note that the self.path has a Train sub-string staring with an uppercase T, while elif is comparing it with lower-case train, which evaluates to False. This can be fixed by changing the elif as:

elif 'train'.lower() in self.path.lower():
    self.img_path = "/home/ubuntu/lecttue-diagonosis/YangDongJae/ai/data/Training/images/"
    self.lab_path = "/home/ubuntu/lecttue-diagonosis/YangDongJae/ai/data/Training/annotations/"
    self.label = list(sorted(os.listdir(self.lab_path)))
    self.imgs = list(sorted(os.listdir(self.img_path)

You may also change the if statement for validation case similarly.