Iterating through the generator crashes when I add normalization

vision
1

Hello,

I had a piece of code that was working fine but when I added a normalization step in my “transforms”, it crashed.

Here’s my code for creating the generator :

data_transforms_train = transforms.Compose([
    transforms.Resize((512, 512)),
    transforms.RandomVerticalFlip(),
    transforms.RandomHorizontalFlip(),
    transforms.ToTensor(),
    transforms.Normalize(mean=[0.8979], std=[0.3025])
])
    
params = {'batch_size': 1,
          'shuffle': True,
          'num_workers': 0}

training_set = Dataset(partition['train'], labels, transform=data_transforms_train)
training_generator = DataLoader(training_set, **params)

Again if I remove the line “transforms.Normalize(mean=[0.8979], std=[0.3025])”, everything goes back to working fine.

Any suggestion on what could be causing this ?

Thanks !

2

Hi,

What is the error that you get? Have you tried putting the normalize before the ToTensor() ?

3

Hello @albanD,

I try running the following in a jupyter notebook :

for test_images, test_labels in training_generator:  
    sample_image = test_images[0]   
    sample_label = test_labels[0]

And I just get a message that the kernel crashed and it will be restarting.

4

It is very hard to say without more informations.
You might want to run it outside of the notebook to get more informations.