```
def model_test():
pyro.sample('Categorical', dist.Categorical(probs=torch.tensor([0.5,0.5])))
pyro.sample('Uniform', dist.Uniform(0,1))
pyro.sample('Bernoulli', dist.Bernoulli(0.1))
pyro.sample('Normal', dist.Normal(1.,1.))
with pyro.plate('data', 3):
val = pyro.sample('obs', dist.Normal(1., 1.))
return val
conditioned_model = pyro.condition(model_test, data={
"obs": torch.tensor([1.,0.,1.])
})
pyro.clear_param_store()
kernel = NUTS(conditioned_model)
posterior = MCMC(kernel, num_samples=2, warmup_steps=1)
posterior.run();
```

`posterior.get_samples()`

returns `{'Normal': tensor([0.7652, 0.2905]), 'Uniform': tensor([0.4800, 0.6557])}`

Why there are no samples from `Categorical`

and `Bernoulli`

? How can I get them?