Does anyone have any detailed tips, walkthrus, or tutorials on how to profile @PyTorch code running on the GPU?
I'm trying to optimize efficientnet and want to see exactly where the time is spent.
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There’s a tensorboard callback in fastai. You could probably model adding parameter activations after the code that plots gradient info. I’ve been thinking about adding it myself but haven’t yet.
