Files
ray/python/ray/internal/internal_api.py
T

65 lines
2.1 KiB
Python

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)