I’m trying to do some program synthesis in Julia. This means generating a lot of programs (Julia
Exprs) evaluating them, and scoring them. These Expressions can create new types, structs, functions, etc. The most reasonable way to do this seems to be to dynamically create a new module. As far as I can tell, creating a module is permanent. Hence it seems like this will inevitably produce memory leaks. Is this true? If so, is there a way around this? Is there a better alternative? Below is a toy example to demonstrate what I mean, which does indeed accumulate increasing amounts of memory:
function genprog(n = 10)
for i = 1:n
y = rand()
mdname = gensym()
expr = :(module $mdname
f(x) = 2*x + $y
m = @show eval(expr)
@show Base.invokelatest(m.f, 3))
To try to avoid the XY Problem , could you elaborate a bit on what you are generating all this code for? Is it some sort of genetic algorithm? Without knowing any of this, it seems like you might get better results from building and evaluating data structures rather than generating code.
I am doing Bayesian program synthesis, which means to generate programs that are likely to have to have generate data. This is not quite the same as genetic programming but there are many similarities. I have an internal DSL that I compile to Julia. I could of course write an interpreter for my DSL, but I am hoping to make use of Julia’s compiler instead.
Hey, can you update on how you proceeded with this? I’m in a similar situation.
I didn’t find a very good solution. I ended up building an interpreter.
One solution is to use Julia’s parallelism features to execute the module in a new Julia instance and then kill it.
There’s also GitHub - MasonProtter/StaticModules.jl: Static module-like namespaces for julia, which might help but when I looked into it it didn’t seem like it quite had what I needed.
Another solution might be to use Julia’s interpreter
Hello @zennatavares, how did you end up solving this?
I have exactly the same challenge myself now, which is how I searched and found this thread.