Im using pyro.plate.
And have an inquiry about assigning values
with pyro.plate("betas", 5): loc = pyro.param("loc", torch.tensor(0.)) scales = pyro.param("scales", torch.tensor(1.)) betas = pyro.sample("beta", dist.Normal(locs, scales))
If I do this, then I have 5 betas. But all of betas are from “the same” distribution which is N(0,1).
What should I do if I were to give 5 betas each different distribution parameter?
I tried for loop to do this. But it is too slow I think
Is there any recommended way for this?