import ray.worker from ray import profiling __all__ = ["free", "global_gc"] def global_gc(): """Trigger gc.collect() on all workers in the cluster.""" worker = ray.worker.get_global_worker() worker.core_worker.global_gc() def free(object_ids, local_only=False, delete_creating_tasks=False): """Free a list of IDs from object stores. This function is a low-level API which should be used in restricted scenarios. If local_only is false, the request will be send to all object stores. This method will not return any value to indicate whether the deletion is successful or not. This function is an instruction to object store. If the some of the objects are in use, object stores will delete them later when the ref count is down to 0. Examples: >>> x_id = f.remote() >>> ray.get(x_id) # wait for x to be created first >>> free([x_id]) # unpin & delete x globally Args: object_ids (List[ObjectID]): List of object IDs to delete. local_only (bool): Whether only deleting the list of objects in local object store or all object stores. delete_creating_tasks (bool): Whether also delete the object creating tasks. """ worker = ray.worker.get_global_worker() if isinstance(object_ids, ray.ObjectID): object_ids = [object_ids] if not isinstance(object_ids, list): raise TypeError("free() expects a list of ObjectID, got {}".format( type(object_ids))) # Make sure that the values are object IDs. for object_id in object_ids: if not isinstance(object_id, ray.ObjectID): raise TypeError("Attempting to call `free` on the value {}, " "which is not an ray.ObjectID.".format(object_id)) if ray.worker._mode() == ray.worker.LOCAL_MODE: worker.local_mode_manager.free(object_ids) return worker.check_connected() with profiling.profile("ray.free"): if len(object_ids) == 0: return worker.core_worker.free_objects(object_ids, local_only, delete_creating_tasks)