Hi all,

I am trying to compute the posterior p(z|x) for this very simple model, and for some reason I do not understand what I am doing wrong (I am discovering this package). Generating data from this model seems to be working, MCMC sampling won’t work.

Here is my model:

```
def pyro_mdl(data):
# with pyro.plate('data', len(data)):
cell_type = pyro.sample('cell_type', dist.Categorical(dataset.probas))
z = pyro.sample('z', pyro.distributions.MultivariateNormal(dataset.mus[cell_type],
dataset.sigmas[cell_type]))
exp_z = z.exp()
x = pyro.sample('x', pyro.distributions.Poisson(rate=exp_z), obs=data)
return x
```

The parameters have already been fitted (I am mostly interested in MCMC right now). When I try to perform MCMC using:

```
kernel = HMC(pyro_mdl, adapt_step_size=True, jit_compile=True, )
mcmc_run = MCMC(kernel, num_samples=500, warmup_steps=300).run(data=x)
```

I get the following error! “TypeError: only integer tensors of a single element can be converted to an index”

Do you have an idea what I have been doing wrong?