[Core] Ability to specify resource requirements on Actor methods

[jfaust]

Description

Currently it's possible to specify resource requirements for Actors:

@ray.remote(memory=1)
class Actor:
  def do_work(...):
    ...

It would be useful to also be able to specify resource requirements on the Actor's methods. Something like:

@ray.remote(memory=1)
class Actor:
  @ray.remote(memory=10)
  def do_work(...):
    ...

Currently to work around it I can create a separate task:

@ray.remote(memory=10)
def do_work(actor, ...):
  return ray.get(actor.do_work(...))

This is not super intuitive, and ends up returning retrieving the results in that task in order to return them, which is not ideal.

I was told to tag @rkooo567

Use case

Initially asked here: https://discuss.ray.io/t/specifying-extra-resources-for-functions-tasks-running-inside-an-actor/12265

PyTorch initialization is costly, so we're keeping an Actor running with the models loaded in memory. We can specify resource constraints on the Actor (in our case a custom gpu_memory resource), however the methods on the Actor will consume more resources, and we don't want to preallocate those to the Actor for a host of reasons.