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Missing performance numbers in the paper #13

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Mut1nyJD opened this issue Jul 27, 2022 · 0 comments
Open

Missing performance numbers in the paper #13

Mut1nyJD opened this issue Jul 27, 2022 · 0 comments

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@Mut1nyJD
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Mut1nyJD commented Jul 27, 2022

First off congratulation to this amazing work. I think you managed to find the closing gap to make generative Deep learning relevant for real-world application, besides being just a nice toy as previous work in this area.

However to truly judge the performance of your approach I have to say I was a bit disappointed after reading your paper there was not a single note on execution time for either training or more crucial actually sampling of a single final image.

Would you be able to provide some numbers on how long a sample generation takes for a 4kx1k images with 256^2 patch size and on which setup?

Also if possible could you also shed some light on training times and which setup was used.

Thank you!

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