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* create guide gallery for Tune * mods * ok * fix * fix_up_gallery * ok * Apply suggestions from code review Co-Authored-By: Sven Mika <sven@anyscale.io> * Apply suggestions from code review Co-Authored-By: Sven Mika <sven@anyscale.io> Co-authored-by: Sven Mika <sven@anyscale.io>
39 lines
1.0 KiB
ReStructuredText
39 lines
1.0 KiB
ReStructuredText
Tune Guides and Tutorials
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=========================
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Tune takes a user-defined Python function or class and evaluates it on a set of hyperparameter configurations.
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Each hyperparameter configuration evaluation is called a *trial*, and multiple trials are run in parallel. Configurations are either generated by Tune or drawn from a user-specified **search algorithm**. The trials are scheduled and managed by a **trial scheduler**.
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.. image:: /images/tune-api.svg
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.. customgalleryitem::
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:tooltip: Getting started with Tune.
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:figure: /images/tune.png
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:description: :doc:`plot_tune-tutorial`
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.. customgalleryitem::
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:tooltip: A simple guide to Population-based Training
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:figure: /images/tune-pbt-small.png
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:description: :doc:`plot_tune-advanced-tutorial`
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.. customgalleryitem::
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:tooltip: Distributed Tuning
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:figure: /images/tune.png
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:description: :doc:`plot_tune-distributed`
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.. toctree::
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:hidden:
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plot_tune-tutorial.rst
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plot_tune-advanced-tutorial.rst
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plot_tune-distributed.rst
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.. :figure: /images/param_actor.png
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