mirror of
https://github.com/vale981/ray
synced 2025-03-06 18:41:40 -05:00
cd5218f831
Replaces #24225 and adds example navigation Signed-off-by: Max Pumperla <max.pumperla@googlemail.com>
371 lines
10 KiB
ReStructuredText
371 lines
10 KiB
ReStructuredText
.. _tune-examples-ref:
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========
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Examples
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========
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.. tip:: Check out :ref:`the Tune User Guides <tune-guides>` To learn more about Tune's features in depth.
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.. _tune-recipes:
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ML Framework Examples
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---------------------
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Ray Tune integrates with many popular machine learning frameworks.
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Here you find a few practical examples showing you how to tune your models.
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At the end of these guides you will often find links to even more examples.
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.. panels::
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:container: container pb-4
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:column: col-md-4 px-2 py-2
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:img-top-cls: pt-5 w-75 d-block mx-auto
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---
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:img-top: /images/tune-sklearn.png
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+++
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.. link-button:: tune-sklearn
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:type: ref
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:text: How To Use Tune's Scikit-Learn Adapters?
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/keras.png
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+++
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.. link-button:: tune-mnist-keras
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:type: ref
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:text: How To Use Tune With Keras & TF Models
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/pytorch_logo.png
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+++
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.. link-button:: tune-pytorch-cifar-ref
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:type: ref
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:text: How To Use Tune With PyTorch Models
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/pytorch_lightning_small.png
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+++
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.. link-button:: tune-pytorch-lightning-ref
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:type: ref
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:text: How To Tune PyTorch Lightning Models
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/mxnet_logo.png
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+++
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.. link-button:: tune-mxnet-example
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:type: ref
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:text: How To Tune MXNet Models
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/serve.svg
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+++
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.. link-button:: tune-serve-integration-mnist
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:type: ref
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:text: Model Selection & Serving With Ray Serve
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /rllib/images/rllib-logo.png
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.. link-button:: tune-rllib-example
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:type: ref
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:text: Tuning RL Experiments With Ray Tune & Ray Serve
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/xgboost_logo.png
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.. link-button:: tune-xgboost-ref
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:type: ref
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:text: A Guide To Tuning XGBoost Parameters With Tune
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/lightgbm_logo.png
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.. link-button:: tune-lightgbm-example
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:type: ref
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:text: A Guide To Tuning LightGBM Parameters With Tune
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/horovod.png
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.. link-button:: tune-horovod-example
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:type: ref
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:text: A Guide To Tuning Horovod Parameters With Tune
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/hugging.png
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.. link-button:: tune-huggingface-example
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:type: ref
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:text: A Guide To Tuning Huggingface Transformers With Tune
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/mlflow.png
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.. link-button:: tune-mlflow-ref
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:type: ref
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:text: Using MLflow Tracking & AutoLogging with Tune
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:classes: btn-link btn-block stretched-link
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Experiment Tracking Examples
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----------------------------
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Ray Tune integrates with some popular Experiment tracking and management tools,
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such as CometML, or Weights & Biases. If you're interested in learning how
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to use Ray Tune with Tensorboard, you can find more information in our
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:ref:`Guide to logging and outputs <tune-logging>`.
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.. panels::
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:container: container pb-4
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:column: col-md-4 px-2 py-2
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:img-top-cls: pt-5 w-75 d-block mx-auto
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---
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:img-top: /images/comet_logo_full.png
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.. link-button:: tune-comet-ref
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:type: ref
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:text: Using Comet with Ray Tune For Experiment Management
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:classes: btn-link btn-block stretched-link
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---
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:img-top: /images/wandb_logo.png
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.. link-button:: tune-wandb-ref
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:type: ref
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:text: Tracking Your Experiment Process Weights & Biases
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:classes: btn-link btn-block stretched-link
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Hyperparameter Optimization Framework Examples
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----------------------------------------------
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Tune integrates with a wide variety of hyperparameter optimization frameworks
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and their respective search algorithms. Here you can find detailed examples
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on each of our integrations:
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.. panels::
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:container: container pb-4
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:column: col-md-4 px-2 py-2
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:img-top-cls: pt-5 w-75 d-block mx-auto
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---
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:img-top: ../images/ax.png
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.. link-button:: ax_example
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:type: ref
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:text: How To Use Tune With Ax
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/dragonfly.png
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.. link-button:: dragonfly_example
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:type: ref
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:text: How To Use Tune With Dragonfly
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/skopt.png
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.. link-button:: skopt_example
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:type: ref
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:text: How To Use Tune With Scikit-Optimize
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/hyperopt.png
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.. link-button:: hyperopt_example
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:type: ref
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:text: How To Use Tune With HyperOpt
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/bayesopt.png
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.. link-button:: bayesopt_example
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:type: ref
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:text: How To Use Tune With BayesOpt
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/flaml.png
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.. link-button:: flaml_example
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:type: ref
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:text: How To Use Tune With BlendSearch and CFO
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/bohb.png
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.. link-button:: bohb_example
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:type: ref
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:text: How To Use Tune With TuneBOHB
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/nevergrad.png
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.. link-button:: nevergrad_example
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:type: ref
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:text: How To Use Tune With Nevergrad
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/optuna.png
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.. link-button:: optuna_example
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:type: ref
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:text: How To Use Tune With Optuna
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/zoopt.png
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.. link-button:: zoopt_example
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:type: ref
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:text: How To Use Tune With ZOOpt
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/sigopt.png
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.. link-button:: sigopt_example
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:type: ref
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:text: How To Use Tune With SigOpt
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:classes: btn-link btn-block stretched-link
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---
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:img-top: ../images/hebo.png
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.. link-button:: hebo_example
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:type: ref
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:text: How To Use Tune With HEBO
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:classes: btn-link btn-block stretched-link
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.. _tune-general-examples:
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Other Examples
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--------------
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- :doc:`/tune/examples/includes/tune_basic_example`: Simple example for doing a basic random and grid search.
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- :doc:`/tune/examples/includes/async_hyperband_example`: Example of using a simple tuning function with
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AsyncHyperBandScheduler.
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- :doc:`/tune/examples/includes/hyperband_function_example`:
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Example of using a Trainable function with HyperBandScheduler.
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Also uses the AsyncHyperBandScheduler.
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- :doc:`/tune/examples/includes/pbt_function`:
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Example of using the function API with a PopulationBasedTraining scheduler.
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- :doc:`/tune/examples/includes/pb2_example`: Example of using the Population-based Bandits (PB2) scheduler.
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- :doc:`/tune/examples/includes/logging_example`: Example of custom loggers and custom trial directory naming.
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- :doc:`/tune/examples/includes/genetic_example`: Optimizing the Michalewicz function using the contributed
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GeneticSearch algorithm with AsyncHyperBandScheduler.
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.. _tune-exercises:
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Exercises
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---------
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Learn how to use Tune in your browser with the following Colab-based exercises.
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.. raw:: html
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<table>
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<tr>
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<th class="tune-colab">Exercise Description</th>
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<th class="tune-colab">Library</th>
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<th class="tune-colab">Colab Link</th>
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</tr>
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<tr>
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<td class="tune-colab">Basics of using Tune.</td>
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<td class="tune-colab">TF/Keras</td>
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<td class="tune-colab">
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<a href="https://colab.research.google.com/github/ray-project/tutorial/blob/master/tune_exercises/exercise_1_basics.ipynb" target="_parent">
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Tune Tutorial"/>
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</a>
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</td>
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</tr>
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<tr>
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<td class="tune-colab">Using Search algorithms and Trial Schedulers to optimize your model.</td>
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<td class="tune-colab">Pytorch</td>
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<td class="tune-colab">
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<a href="https://colab.research.google.com/github/ray-project/tutorial/blob/master/tune_exercises/exercise_2_optimize.ipynb" target="_parent">
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Tune Tutorial"/>
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</a>
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</td>
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</tr>
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<tr>
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<td class="tune-colab">Using Population-Based Training (PBT).</td>
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<td class="tune-colab">Pytorch</td>
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<td class="tune-colab">
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<a href="https://colab.research.google.com/github/ray-project/tutorial/blob/master/tune_exercises/exercise_3_pbt.ipynb" target="_parent">
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Tune Tutorial"/>
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</a>
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</td>
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</tr>
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<tr>
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<td class="tune-colab">Fine-tuning Huggingface Transformers with PBT.</td>
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<td class="tune-colab">Huggingface Transformers/Pytorch</td>
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<td class="tune-colab">
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<a href="https://colab.research.google.com/drive/1tQgAKgcKQzheoh503OzhS4N9NtfFgmjF?usp=sharing" target="_parent">
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Tune Tutorial"/>
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</a>
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</td>
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</tr>
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<tr>
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<td class="tune-colab">Logging Tune Runs to Comet ML.</td>
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<td class="tune-colab">Comet</td>
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<td class="tune-colab">
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<a href="https://colab.research.google.com/drive/1dp3VwVoAH1acn_kG7RuT62mICnOqxU1z?usp=sharing" target="_parent">
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Tune Tutorial"/>
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</a>
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</td>
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</tr>
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</table>
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Tutorial source files `can be found here <https://github.com/ray-project/tutorial>`_.
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