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Usage example of RNN with large inputs #12
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@adicirstei I can offer you my solution, but it requires you to modify source code. In |
Thanks @zgrkpnr! I'll give it a try. Hope I'll be able to compile it. |
@zgrkpnr do you remember what was the size of that list when you got OutOfMemory? Looking at the code quickly, it feels this should actually be a This change could save roughly 4 bytes per element. |
@smoothdeveloper Let's say our model has 900,000 parameters to optimize (which is quite normal for deep structures). 100 minibacthes and 10 Epochs for each brings us 100 x 10 x 900,000 single precision floating points of the size 3.4 b bytes. Roughly 3GB. I may be wrong, of course. @adicirstei If the solution works, let me know. |
We might want to switch to Resize array as suggested on #12
Perhaps we should add an option to control collecting history? Lines 370 to 384 in 366daa7
It could default on but allow people with large models to disable without having to recompile. Does anyone have an optimization real use case they could share? We could potentially speed it up as well. |
Hi,
I would like to use large inputs for training a phrase generating model and I tried to adapt the example on the website but of course I get an
OutOfMemoryException
What would be a good approach to this kind of task?
Thanks,
Adrian
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