Performance guide for PyTorch

Hi there,
I like your flexible framework very much!

I’m just wondering is there any performance guide like
so that I can follow and accelerate my model, both training and testing.

One possible solution is to delete the tensors you don’t need any more, if the reference count goes to 0, then we can free some GPU memory resources? Will this also lead to some speed-up?

Thank you very much in advance!

It’s more than just a bit rough, but you could check out the bottleneck documentation.

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Hi, I tried this link, get the very similar issue in
I’m actually asking about some common tricks to improve the speed, like that in the link I posted.

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