MCMC does not return any samples

Misc.
1

I am doing inference on a simple model and it seems like MCMC does sampling, however, .get_sampels() gives me an empty dictionary.

def model_simple():
    mean = pyro.sample('mean', pyro.distributions.Gamma(9.0, 0.5))
    lemonade = pyro.sample('lemonade', pyro.distributions.Poisson(mean))
    return lemonade, mean

def model_correct_weekend_only():
    lemonade = pyro.sample('lemonade', pyro.distributions.Poisson(6.0))
    return lemonade


def model_simple_conditioned(model, x):
    return pyro.condition(model, data={'lemonade': x})


def inference_task1():
    data = torch.stack([model_correct_weekend_only() for _ in range(100)])

    nuts_kernel = NUTS(model_simple_conditioned, jit_compile=False)
    mcmc = MCMC(nuts_kernel,
                num_samples=1000,
                warmup_steps=100,
                num_chains=2)
    mcmc.run(model_simple, data)
    samples = mcmc.get_samples()
2

@timudk You need to call the model to actually run it.

def model_simple_conditioned(model, x):
    return pyro.condition(model, data={'lemonade': x})()