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[tune] Added WandbLogger (#9725)
Co-authored-by: Richard Liaw <rliaw@berkeley.edu> Co-authored-by: Kai Fricke <kai@anyscale.com>
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co-authored by
Richard Liaw
Kai Fricke
parent
68f3fec744
commit
619e44e54a
@@ -53,6 +53,11 @@ Take a look at any of the below tutorials to get started with Tune.
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:figure: /images/xgboost_logo.png
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:description: :doc:`A guide to tuning XGBoost parameters with Tune <tune-xgboost>`
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.. customgalleryitem::
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:tooltip: Use Weights & Biases within Tune.
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:figure: /images/wandb_logo.png
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:description: :doc:`Track your experiment process with the Weights & Biases tools <tune-wandb>`
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.. raw:: html
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@@ -69,6 +74,7 @@ Take a look at any of the below tutorials to get started with Tune.
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tune-pytorch-cifar.rst
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tune-pytorch-lightning.rst
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tune-xgboost.rst
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tune-wandb.rst
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Colab Exercises
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---------------
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@@ -0,0 +1,35 @@
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.. _tune-wandb:
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Using Weights & Biases with Tune
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================================
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`Weights & Biases <https://www.wandb.com/>`_ (Wandb) is a tool for experiment
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tracking, model optimizaton, and dataset versioning. It is very popular
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in the machine learning and data science community for its superb visualization
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tools.
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.. image:: /images/wandb_logo_full.png
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:height: 80px
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:alt: Weights & Biases
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:align: center
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:target: https://www.wandb.com/
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Ray Tune currently offers two lightweight integrations for Weights & Biases.
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One is the :ref:`WandbLogger <tune-wandb-logger>`, which automatically logs
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metrics reported to Tune to the Wandb API.
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The other one is the :ref:`@wandb_mixin <tune-wandb-mixin>` decorator, which can be
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used with the function API. It automatically
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initializes the Wandb API with Tune's training information. You can just use the
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Wandb API like you would normally do, e.g. using ``wandb.log()`` to log your training
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process.
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Please :doc:`see here for a full example </tune/examples/wandb_example>`.
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.. _tune-wandb-logger:
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.. autoclass:: ray.tune.integration.wandb.WandbLogger
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.. _tune-wandb-mixin:
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.. autofunction:: ray.tune.integration.wandb.wandb_mixin
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