Imagine I have a scalar T
, this T is gonna be used as a threshold in my network. i.e.
TensorA = torch.where(TensorB > T*Means, Ones, Zeros)
.
Right now I have T = torch.tensor(1.0)
, but I want to give it the ability to change and be learnable.
Is the way to do that?
In other words, how can I wrap it in a way to be learnable?
Hmmm i dont think that is enough…
I think i need to do something like this:
LearnableParameter = nn.Parameter(Parameter, requires_grad=True)
but im not %100 sure
it would be helpful if someone can confirm it
If you use nn.Parameter it will Be learnable
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