Hi,

I have a noob question. I am going over Introduction to Pyro — Pyro Tutorials 1.8.1 documentation and I see that the hyperparameters in the model and the variational parameters in the guide are different in the given example. For example, `a`

is defined in `custom_guide`

as

```
a_loc = pyro.param('a_loc', lambda: torch.tensor(0.))
a_scale = pyro.param('a_scale', lambda: torch.tensor(1.), constraint=constraints.positive)
a = pyro.sample("a", dist.Normal(a_loc, a_scale))
```

and in `model`

as

```
a = pyro.sample("a", dist.Normal(0., 10.))
```

Furthermore, I see in the same example that the distributions for `sigma`

are different in the model and guide (It is `Uniform`

in the model and `Normal`

in the guide)

I have two questions following this:

- Is there any particular reason why distribution parameters/distributions are different in the guide and model?
- When should I consider choosing the distribution parameters/distributions in the model and guide differently?