Using lightweight-gan with Colab ? about lightweight-gan

[lucidrains]

@7Khalil sure! I mean, you just have to download all the images to a folder and run one command

[lucidrains]

@7Khalil the dataset size doesn't determine the amount of GPU memory used, it's the batch size and image resolution that are the determinants

[ClashLuke]

pin_memory=True is set to True. This is a trick used to disable constant freeing and reallocating of memory by PyTorch, therefore improving the training speed by a bit. Usually, pinning the memory improves the speeds by something around 1% to 15%. If you're facing GPU memory issues, perhaps turning this flag off would be a good first step.

[lucidrains]

@7Khalil do you really think it needs a colab?

[lil-km]

@lucidrains actualy i have tried it, and i got with a dataset of ~1300 images, i got GPU memory overflow. after reading your comment i the tried it with a smaller dataset with 500 images and it seems to work well.

[lucidrains]

@7Khalil ohh, what sized images did you try to train? you shouldn't overflow with anything below or at 512x512

[lil-km]

@lucidrainsit seems weird, because both datasets that i used are 1024px resolution. wondering why ?!

[lil-km]

Ok, @ClashLuke thanks.