I’m struggling to work effectively with models that are using the `AutoLaplaceApproximation`

guide. Unlike the (mutlivariate) normal approximations, you cannot just pull quantiles from the estimated posterior directly, and I am unable to find usage examples in the docs.

I did find the following approach for sampling from the posterior here:

```
guide = autoguides.AutoLaplaceApproximation(my_model)
<fit model>
laplace_guide = guide.laplace_approximation()
pred = pyro.infer.Predictive(laplace_guide, num_samples=1000)
```

but it does not work directly with `my_model`

in my case because the model itself takes 4 tensors of data as arguments. However, when I try and pass the data to the `laplace_approximation`

method:

```
laplace_guide = guide.laplace_approximation(*data)
```

I get a `RuntimeError`

```
RuntimeError: One of the differentiated Tensors does not require grad
```

Does anyone have a link to a fully worked example? That is, something that shows how to extract inference from a fitted model using the `AutoLaplaceApproximation`

or similar guides.