class_docstr: Management class for Ray actors and actor tasks.
  
  This class provides an event-based management interface for actors, and
  actor tasks.
  
  The manager can be used to start actors, stop actors, and schedule and
  track task futures on these actors.
  The manager will then invoke callbacks related to the tracked entities.
  
  For instance, when an actor is added with
  :meth:`add_actor() <RayActorManager.add_actor>`,
  a :ref:`TrackedActor <ray.air.execution._internal.tracked_actor.TrackedActor`
  object is returned. An ``on_start`` callback can be specified that is invoked
  once the actor successfully started. Similarly, ``on_stop`` and ``on_error``
  can be used to specify callbacks relating to the graceful or ungraceful
  end of an actor's lifetime.
  
  When scheduling an actor task using
  :meth:`schedule_actor_task()
  <ray.air.execution._internal.actor_manager.RayActorManager.schedule_actor_task>`,
  an ``on_result`` callback can be specified that is invoked when the task
  successfully resolves, and an ``on_error`` callback will resolve when the
  task fails.
  
  The RayActorManager does not implement any true asynchronous processing. Control
  has to be explicitly yielded to the event manager via :meth:`RayActorManager.next`.
  Callbacks will only be invoked when control is with the RayActorManager, and
  callbacks will always be executed sequentially in order of arriving events.
  
  Args:
      resource_manager: Resource manager used to request resources for the actors.
  
  Example:
  
      .. code-block:: python
  
          from ray.air.execution import ResourceRequest
          from ray.air.execution._internal import RayActorManager
  
          actor_manager = RayActorManager()
  
          # Request an actor
          tracked_actor = actor_manager.add_actor(
              ActorClass,
              kwargs={},
              resource_request=ResourceRequest([{"CPU": 1}]),
              on_start=actor_start_callback,
              on_stop=actor_stop_callback,
              on_error=actor_error_callback
          )
  
          # Yield control to event manager to start actor
          actor_manager.next()
  
          # Start task on the actor (ActorClass.foo.remote())
          tracked_actor_task = actor_manager.schedule_actor_task(
              tracked_actor,
              method_name="foo",
              on_result=task_result_callback,
              on_error=task_error_callback
          )
  
          # Again yield control to event manager to process task futures
          actor_manager.wait()
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docstr: Returns True if the actor has been started.
  
  Args:
      tracked_actor: Tracked actor object.
code: def is_actor_started(self, tracked_actor: TrackedActor) -> bool:
      """Returns True if the actor has been started.
  
      Args:
          tracked_actor: Tracked actor object.
      """
      return (
          tracked_actor in self._live_actors_to_ray_actors_resources
          and tracked_actor.actor_id not in self._failed_actor_ids
      )
  
imports: import logging
  import random
  import time
  import uuid
  from collections import defaultdict, Counter
  from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Type, Union
  import ray
  from ray.air.execution._internal.event_manager import RayEventManager
  from ray.air.execution.resources import AcquiredResources, ResourceManager, ResourceRequest
  from ray.air.execution._internal.tracked_actor import TrackedActor
  from ray.air.execution._internal.tracked_actor_task import TrackedActorTask
  from ray.exceptions import RayTaskError, RayActorError
label_desc: Use image node_id 23 for calling the RayActorManager obj's underlying member method code with example usage: obj.is_actor_started(tracked_actor) and returns: unknown