Comments (3)
Hi @mahdi259
I think for QuantIdentity
the answer is just to use Uint8ActPerTensorFloat
when initialising QuantIdentity
with optional argument act_quant=Uint8ActPerTensorFloat
instead of the default int8 - which you can see here
brevitas/src/brevitas/nn/quant_activation.py
Line 106 in 2004568
For weights in e.g. QuantLinear
I think it would be less common to use unsigned integers, so I don't think there's a datatype available built-in, but you could experiment with that by extending the Int8
weight data type
I hope that helps!
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Thanks @capnramses . That's it. One more question. I have read ULPPACK paper that performs inner product of unsigned numbers, i.e. unsigned inputs and weights. I agree that it's odd to have unsigned weights. Do you know how they use ULPPACK in networks like ResNet?
Thanks
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I haven't read that paper I'm sorry! I think that might be off topic for the repo, so I'm going to close this Issue.
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