code: def register_trainable(
      name: str, trainable: Union[Callable, Type], warn: bool = True
  ):
      """Register a trainable function or class.
  
      This enables a class or function to be accessed on every Ray process
      in the cluster.
  
      Args:
          name: Name to register.
          trainable: Function or tune.Trainable class. Functions must
              take (config, status_reporter) as arguments and will be
              automatically converted into a class during registration.
      """
  
      from ray.tune.trainable import wrap_function
      from ray.tune.trainable import Trainable
  
      if isinstance(trainable, type):
          logger.debug("Detected class for trainable.")
      elif isinstance(trainable, FunctionType) or isinstance(
          trainable, partial
      ):
          logger.debug("Detected function for trainable.")
          trainable = wrap_function(trainable, warn=warn)
      elif callable(trainable):
          logger.info(
              "Detected unknown callable for trainable. Converting to class."
          )
          trainable = wrap_function(trainable, warn=warn)
  
      if not issubclass(trainable, Trainable):
          raise TypeError(
              "Second argument must be convertable to Trainable",
              trainable,
          )
      _global_registry.register(TRAINABLE_CLASS, name, trainable)
  
imports: import atexit
  import logging
  from functools import partial
  from types import FunctionType
  from typing import Callable, Optional, Type, Union
  import ray
  import ray.cloudpickle
  from ray.experimental.internal_kv import _internal_kv_get, _internal_kv_initialized, _internal_kv_put, _internal_kv_del
  from ray.tune.error import TuneError
  from ray.util.annotations import DeveloperAPI
label_desc: Use image node_id 5 for calling a global function with example usage: register_trainable(name, trainable, warn) without return types