Currently implemented operations on Turing models:

• fix / unfix (equivalent to the do-operator)
• condition / decondition
• generated_quantities
• predict ( could be implemented using fix, see PR)

@model function demo1()
  x ~ Normal()
  z ~ Normal()
  y = x - z
  return y
end


m = demo1()
conditioned_m = condition(m, (x=1))
fixed_m = fix(m, (x=1))
ret = generated_quantities(m, (x=1.0, z=2.0))
predict(m, chain) 

Proposed new model operation

• returned_quantities

This will replace and unify two current syntax submodel and generated_quantities. A reviewer for a Turing.jl preprint has pointed out that the generated_quantities is confusing due to the name clash with Stan's generated quantities block, but with different motivations (Stan's generated quantities are entirely motivated for performance while ours is a return statement that can be used for many purposes).

Another consideration is that submodel and generated_quantities have almost identical semantics from the user's perspective: both syntaxes obtain the returned variables of a model. However, the submodel syntax requires some special treatment for inference purposes, i.e., storing all submodel random variables in the parent model's VarInfo. This distinction doesn't matter much for users and won't deserve two separate syntaxes.

@model function demo2a(x, y) 
   @submodel a  = demo1(x)
   return y ~ Uniform(0, abs(a)) 
end

# with the proposed syntax, this becomes: 

@model function demo2b(x, y) 
   a = @returned_quantities(demo1()) 
   return y ~ Uniform(0, a) 
end 

In addition, the generated_quantites becomes

returned_quantities(model::Model, parameters::NamedTuple)
returned_quantities(model::Model, values, keys)