How to save cpu memory?

vision
#1

I currently load data with toarch.load because they are saved as a pickle. Pickle can only load everything once into the memory. Then, I work on this data using a data loader and save this data in list.

data = torch.load('clean_data')
test_loader = dataloader(data, batch_size=32, shuffle=True)

result = []
for img, label in test_loader:
    # do somehting
    result.append([img.cpu(), label.cpu()])

torch.save(result)

So I double use the cpu memory and I dont have so much available.
I want to save CPU memory. Does anybody has any idea? For example, how to load dynamically this pickle file? Or should I focus on saving the pickle file dynamically?

I am grateful for any help. Thanks