hiro/ray
1
0
Fork 0
mirror of https://github.com/vale981/ray synced 2025-03-05 10:01:43 -05:00
Code Issues Projects Releases Packages Wiki Activity Actions

Minor update on the key concept explanation (#28032)

Browse source
This commit is contained in:
Amin Allahyar 2022-08-26 19:57:58 +02:00 • committed by GitHub
parent 6c69ee9a97
commit 455fa664e5
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
1 changed files with 1 additions and 1 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

2
doc/source/tune/key-concepts.rst
View file

@ -15,7 +15,7 @@ First, you define the hyperparameters you want to tune in a `search space` and p
that specifies the objective you want to tune. that specifies the objective you want to tune.
Then you select a `search algorithm` to effectively optimize your parameters and optionally use a Then you select a `search algorithm` to effectively optimize your parameters and optionally use a
`scheduler` to stop searches early and speed up your experiments. `scheduler` to stop searches early and speed up your experiments.
Together with other configuration, your `trainable`, algorithm, and scheduler are passed into ``Tuner``, Together with other configuration, your `trainable`, search algorithm, and scheduler are passed into ``Tuner``,
which runs your experiments and creates `trials`. which runs your experiments and creates `trials`.
These trials can then be used in `analyses` to inspect your experiment results. These trials can then be used in `analyses` to inspect your experiment results.
The following figure shows an overview of these components, which we cover in detail in the next sections. The following figure shows an overview of these components, which we cover in detail in the next sections.