wehub/ray-project--ray
1
0
Fork 0
Code Issues Pull Requests Actions Deployments Models Agent Notes Packages Projects Releases Wiki Activity

chore: import upstream snapshot with attribution

Browse Source
This commit is contained in:
wehub-resource-sync
2026-07-13 13:17:40 +08:00
commit f1825c8ceb
10096 changed files with 2364182 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
doc/source/tune/examples/includes/async_hyperband_example.rst
+19
View File
@@ -0,0 +1,19 @@
:orphan:
Asynchronous HyperBand Example
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This example demonstrates how to use Ray Tune's Asynchronous Successive Halving Algorithm (ASHA) scheduler
to efficiently optimize hyperparameters for a machine learning model. ASHA is particularly useful for
large-scale hyperparameter optimization as it can adaptively allocate resources and end
poorly performing trials early.
Requirements: `pip install "ray[tune]"`
.. literalinclude:: /../../python/ray/tune/examples/async_hyperband_example.py
See Also
--------
- `ASHA Paper <https://arxiv.org/abs/1810.05934>`_