Is it possible to model a custom dependency structure in the posterior guide between random variables with separate definitions in the model?

Here is an example of what I’d like to accomplish, but I’m not sure how to do that with the naming constraints in the guide.

```
def model(x, options):
gamma_g = numpyro.sample("gamma_g", dist.Gamma(options.conc_g, options.rate_g))
gamma_l = numpyro.sample("gamma_l", dist.Gamma(options.conc_l, gamma_g))
...
return
def guide(x, options):
w_df = numpyro.param("w_df", 1., constraint=constraints.positive)
w_scale = numpyro.param("w_scale", jnp.eye(2), constraint=constraints.lower_cholesky)
# i know the next line is incorrect, but this is where I'm unclear on how to proceed
gamma_joint = numpyro.sample("[gamma_g, gamma_l]", tfpdist.WishartTriL(w_df, w_scale))
```

Could this be accomplished with a `substitute`

call in the guide that replaces `gamma_g`

and `gamma_l`

by their respective sampled values in `gamma_joint`

?