hiro/ray
1
0
Fork 0
mirror of https://github.com/vale981/ray synced 2025-03-06 02:21:39 -05:00
Code Issues Projects Releases Packages Wiki Activity Actions

[tune/docs] Trial executor doc fix (#25440)

Browse source
This commit is contained in:
Kai Fricke 2022-06-03 16:25:38 +01:00 • committed by GitHub
parent 7186cd8b79
commit 313e8730a2
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
1 changed files with 6 additions and 7 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

13
doc/source/tune/tutorials/tune-lifecycle.rst
View file

@ -32,7 +32,7 @@ while Ray Tune trainable "actors" run on any node (either on the same node or on
The driver spawns parallel worker processes (:ref:`Ray actors <actor-guide>`)
that are responsible for evaluating each trial using its hyperparameter configuration and the provided trainable
(see the `trial executor source code <https://github.com/ray-project/ray/blob/master/python/ray/tune/trial_executor.py>`__).
(see the `ray trial executor source code <https://github.com/ray-project/ray/blob/master/python/ray/tune/ray_trial_executor.py>`__).
While the Trainable is executing (:ref:`trainable-execution`), the Tune Driver communicates with each actor
via actor methods to receive intermediate training results and pause/stop actors (see :ref:`trial-lifecycle`).
@ -152,12 +152,11 @@ the following states: ``"PENDING"``, ``"RUNNING"``, ``"PAUSED"``, ``"ERRORED"``,
See the docstring at :ref:`trial-docstring`.
TrialExecutor
~~~~~~~~~~~~~
[`source code <https://github.com/ray-project/ray/blob/master/python/ray/tune/trial_executor.py>`__]
The TrialExecutor is a component that interacts with the underlying execution framework.
It also manages resources to ensure the cluster isn't overloaded. By default,
the TrialExecutor uses Ray to execute trials.
RayTrialExecutor
~~~~~~~~~~~~~~~~
[`source code <https://github.com/ray-project/ray/blob/master/python/ray/tune/ray_trial_executor.py>`__]
The RayTrialExecutor is a component that interacts with the underlying execution framework.
It also manages resources to ensure the cluster isn't overloaded.
See the docstring at :ref:`raytrialexecutor-docstring`.