I’m new to pyro and I’m following the Bayesian Regression - Inference Algorithm (part 2) Tutorial. I tried to build my own model and guide, and I just want to find the value of the weight, bias and noise given some linear data.
I’ll leave here part of my code. I think it’s pretty similar to the one in the tutorial but I get
UserWarning: Encountered NaN: loss when I do
svi.step. Can you help me understand why and what I should change? Thanks.
The data (x=height, y=mass) is normalised.
def model(height, mass): # unit normal priors over the parameters b, w, noise ..... mean = b + w * height # condition on the observed data with pyro.plate("data", len(height)): pyro.sample("obs", dist.Normal(mean, noise), obs=mass) def guide(height, mass): # register variational parameters b_loc, b_scale, w_loc, w_scale, noise_loc .... # sample from normal prior ...