I made this data loader for image colorization and when i tried to run below code it is taking too much time for even one iteration. Can someone please look into this why its taking too much time

```
cuda = torch.device('cuda')
class DATALODER(Dataset):
def __init__(self, root_dir, transform=None):
self.root_dir = root_dir
self.transform = transform
def __len__(self):
return 100
def __getitem__(self, idx):
img_name = os.path.join(self.root_dir,
str(idx) + ".jpg")
image = io.imread(img_name)
gray_img = rgb2gray(image)
lab_img = rgb2lab(image)[:,:,1:]
sample = (gray_img, lab_img)
sample = self.transform(sample)
return sample
class ToTensor(object):
def __call__(self, sample):
gray_img, lab_img = sample
tensor_gray = torch.tensor(gray_img, device=cuda).float()
tensor_label = torch.tensor(lab_img.transpose((2,0,1)), device=cuda).float()
tensor_label = tensor_label.view(1,2, tensor_gray.size()[0], tensor_gray.size()[1])
tensor_gray = tensor_gray.view(1, 1, tensor_gray.size()[0], tensor_gray.size()[1])
return (tensor_gray,tensor_label)
root_dir = "./images/Train/"
my_dataloader = DATALODER(root_dir, ToTensor())
train_data = DataLoader(my_dataloader, batch_size=4, num_workers=2)
for i, temp in enumerate(train_data):
print(i)
if i==1:
break
```