class_docstr: Metadata for an actor class.
  
  Attributes:
      language: The actor language, e.g. Python, Java.
      modified_class: The original class that was decorated (with some
          additional methods added like __ray_terminate__).
      actor_creation_function_descriptor: The function descriptor for
          the actor creation task.
      class_id: The ID of this actor class.
      class_name: The name of this class.
      num_cpus: The default number of CPUs required by the actor creation
          task.
      num_gpus: The default number of GPUs required by the actor creation
          task.
      memory: The heap memory quota for this actor.
      resources: The default resources required by the actor creation task.
      accelerator_type: The specified type of accelerator required for the
          node on which this actor runs.
          See :ref:`accelerator types <accelerator_types>`.
      runtime_env: The runtime environment for this actor.
      scheduling_strategy: Strategy about how to schedule this actor.
      last_export_session_and_job: A pair of the last exported session
          and job to help us to know whether this function was exported.
          This is an imperfect mechanism used to determine if we need to
          export the remote function again. It is imperfect in the sense that
          the actor class definition could be exported multiple times by
          different workers.
      method_meta: The actor method metadata.
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code: def __init__(
      self,
      language,
      modified_class,
      actor_creation_function_descriptor,
      class_id,
      max_restarts,
      max_task_retries,
      num_cpus,
      num_gpus,
      memory,
      object_store_memory,
      resources,
      accelerator_type,
      runtime_env,
      concurrency_groups,
      scheduling_strategy: SchedulingStrategyT,
  ):
      self.language = language
      self.modified_class = modified_class
      self.actor_creation_function_descriptor = (
          actor_creation_function_descriptor
      )
      self.class_name = actor_creation_function_descriptor.class_name
      self.is_cross_language = language != Language.PYTHON
      self.class_id = class_id
      self.max_restarts = max_restarts
      self.max_task_retries = max_task_retries
      self.num_cpus = num_cpus
      self.num_gpus = num_gpus
      self.memory = memory
      self.object_store_memory = object_store_memory
      self.resources = resources
      self.accelerator_type = accelerator_type
      self.runtime_env = runtime_env
      self.concurrency_groups = concurrency_groups
      self.scheduling_strategy = scheduling_strategy
      self.last_export_session_and_job = None
      self.method_meta = _ActorClassMethodMetadata.create(
          modified_class, actor_creation_function_descriptor
      )
  
imports: import inspect
  import logging
  import weakref
  from typing import Any, Dict, List, Optional, Union
  import ray._private.ray_constants
  import ray._private.signature
  import ray._private.worker
  import ray._raylet
  from ray import ActorClassID, Language, cross_language
  from ray._private import ray_option_utils
  from ray._private.async_compat import is_async_func
  from ray._private.auto_init_hook import wrap_auto_init
  from ray._private.client_mode_hook import client_mode_convert_actor, client_mode_hook, client_mode_should_convert
  from ray._private.inspect_util import is_class_method, is_function_or_method, is_static_method
  from ray._private.ray_option_utils import _warn_if_using_deprecated_placement_group
  from ray._private.utils import get_runtime_env_info, parse_runtime_env
  from ray._raylet import STREAMING_GENERATOR_RETURN, ObjectRefGenerator, PythonFunctionDescriptor, raise_sys_exit_with_custom_error_message
  from ray.exceptions import AsyncioActorExit
  from ray.util.annotations import DeveloperAPI, PublicAPI
  from ray.util.placement_group import _configure_placement_group_based_on_context
  from ray.util.scheduling_strategies import PlacementGroupSchedulingStrategy, SchedulingStrategyT
  from ray.util.tracing.tracing_helper import _inject_tracing_into_class, _tracing_actor_creation, _tracing_actor_method_invocation
label_desc: Use image node_id 1 to create a new _ActorClassMetadata object  with example: obj = _ActorClassMetadata(language, modified_class, actor_creation_function_descriptor, class_id, max_restarts, max_task_retries, num_cpus, num_gpus, memory, object_store_memory, resources, accelerator_type, runtime_env, concurrency_groups, scheduling_strategy)