class CustomDataset(Dataset):
    def __init__(self, img_path_list, label, train_mode=True):
        self.img_path_list = img_path_list
        self.label = label
        self.train_mode = train_mode
       
    def __len__(self):
        return len(self.img_path_list)
   
    def __getitem__(self, index):
        image = Image.open(self.img_path_list[index]).convert('RGB')
       
        if self.train_mode:
            image = self.train_transform(image)
            target = np.array(self.label[index])
            target = torch.tensor(target).long()
        else:
            image = self.test_transform(image)
           
        if self.label is not None:
            return image, target
        else:
            return image
   
    # Image Augmentation
    def train_transform(self, image):
        transform_ops = transforms.Compose([
            transforms.ToTensor(),
            transforms.Resize((224,224)),
            #transforms.RandomCrop(25),
            transforms.RandomHorizontalFlip(),
            transforms.ColorJitter(brightness=0.4, contrast=0.4, saturation=0.4, hue=0.1),
           
            # 일반적인 이미지에서 잘 되는 정규화 방법
            transforms.Normalize(mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225))
        ])
        return transform_ops(image)
   
    def test_transform(self, image):
        transform_ops = transforms.Compose([
            transforms.ToTensor(),
            transforms.Resize((32,32)),
            transforms.Normalize(mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225))
        ])
        return transform_ops(image)
   
    def target_transform(self, target):
        transform_ops = transforms.Compose([
            transforms.ToTensor(),
        ])
        return transform_ops(target)
   

이렇게 데이터셋 해놓고 모델 돌리니까 자꾸 'list' object has no attribute 'size' 오류가 나오는데 뭐가 문제일까요..