What is the point of splitting into model and guide?

Noob question. Let’s take the toy example from Example: Toy Mixture Model With Discrete Enumeration — Pyro Tutorials 1.7.0 documentation. There, we have a function for the model and a function for the guide. What would be different, if we put everything into a model like this:

@pyro.infer.config_enumerate
def model(prior, obs, num_obs):
    a = pyro.param("a", prior["A"], constraint=constraints.positive)
    p_A = pyro.sample("p_A", dist.Beta(a[0], a[1]))
    b = pyro.param("b", prior["B"], constraint=constraints.positive)
    p_B = pyro.sample("p_B", dist.Beta(b[:, 0], b[:, 1]).to_event(1))
    c = pyro.param("c", prior["C"], constraint=constraints.positive)
    P_C = pyro.sample("p_C", dist.Beta(c[:, 0], c[:, 1]).to_event(1))
    with pyro.plate("data_plate", num_obs):
        A = pyro.sample("A", dist.Bernoulli(p_A.expand(num_obs)), obs=obs["A"])
        # Vindex used to ensure proper indexing into the enumerated sample sites
        B = pyro.sample(
            "B",
            dist.Bernoulli(Vindex(p_B)[A.type(torch.long)]),
            infer={"enumerate": "parallel"},
        )
        pyro.sample("C", dist.Bernoulli(Vindex(p_C)[B.type(torch.long)]), obs=obs["C"])

and use

def noguide(prior, obs, num_obs):
    pass

Hi @fridental, your model has different priors to the priors in the tutorial. Because your noguide does not provide any help for latent variables p_A, p_B, p_C in your model, SVI won’t work with the above pair. You might want to see SVI tutorial 1 for definitions of model and guide in Pyro.