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
...
```