Pattern: Tree of actors¶
Example use case¶
You want to train 3 models at the same time, while being able to checkpoint/inspect its state.
In this pattern, a collection of Ray worker actors is managed by a supervisory Ray actor.
A single call to the supervisor actor triggers the dispatch of multiple method calls to child actors. The supervisor can process results or update child actors prior to returning.
If the supervisor dies (or the driver), the worker actors are automatically terminated thanks to actor reference counting.
Actors can be nested to multiple levels to form a tree.
@ray.remote(num_cpus=1) class Worker: def work(self): return "done" @ray.remote(num_cpus=1) class Supervisor: def __init__(self): self.workers = [Worker.remote() for _ in range(3)] def work(self): return ray.get([w.work.remote() for w in self.workers]) ray.init() sup = Supervisor.remote() print(ray.get(sup.work.remote())) # outputs ['done', 'done', 'done']