Obliviously
Obliviously
Im not sure how much VRAM you need but you could change the code to load images only batch wise to reduce memory load. Apart from that you could lower...
@rahat-yasir You need a new model for every scale. @cauivy Adjust model.py by removing one scaling layer ``` #n = Conv2d(n, 256, (3, 3), (1, 1), act=None, padding='SAME', W_init=w_init, name='n256s1/2')...
@artificialskills To also answer the original question. For 8x upscaling you do it similar, instead of removing a scaling layer you add one. You probably also have to adjust the...
As far as I know you can't do floating point scaling with the given layers. The easiest way of doing it would be to scale it to the the next...
I changed to Python 3.5.7 and rebuild pyflow with it. It seems to have solved the problem.
First off: You wouldn't necessary change the model to do that. Secondly the program is already doing that as far as i can see.