BMG issue with "Internal compiler error in edge requirements checking:"

Issue Description

Running the simple model below with BMG raises a

beanmachine.ppl.compiler.internal_error.InternalError: Internal compiler error in edge requirements checking:
 Node of type BetaNode is being checked for requirements but the lattice typer is unable to assign it a type. Requirements checking always needs to know the lattice type of a node when checking requirements on its outgoing edges.

Replacing dist.Bernoulli(1 - self.Probability()) by dist.Bernoulli(self.Probability()) removes the error which looks strange (but it is another model…).

Replacing return dist.Beta(self.MetaParameter() + 0.1, self.MetaParameter() + 0.1) by return dist.Beta(0.1, self.MetaParameter() + 0.1) changes the error to ValueError: Beta parents must be positive real-valued

Steps to Reproduce

import beanmachine.ppl as bm
import torch
import torch.distributions as dist


class Model:
    @bm.random_variable
    def MetaParameter(self):
        return dist.Uniform(0, 1)

    @bm.random_variable
    def Probability(self):
        return dist.Beta(self.MetaParameter() + 0.1, self.MetaParameter() + 0.1)

    @bm.random_variable
    def Observation(self):
        return dist.Bernoulli(1 - self.Probability())


model = Model()

samples = bm.inference.BMGInference().infer(
    queries=[model.MetaParameter()],
    observations={model.Observation(): torch.tensor(1)},
    num_samples=1000,
    num_chains=2,
)

Expected Behavior

I would expect the code to run correctly. Is there some documentation on how to add new rules to the lattice typer ?

System Info

Please provide information about your setup

• PyTorch Version (run print(torch.__version__): 1.10.1+cpu
• Python version: 3.8.12 (default, Oct 12 2021, 03:01:40) [MSC v.1916 64 bit (AMD64)]

[sdementen]

I confirm it works when replacing Uniform with Beta, tx a lot!

[sdementen]

Thank you for taking the time to write this detailed comment, very instructive !