wehub-resource-sync
127 lines
3.1 KiB
ReStructuredText
127 lines
3.1 KiB
ReStructuredText
.. _loggers-docstring:
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Tune Loggers (tune.logger)
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==========================
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Tune automatically uses loggers for TensorBoard, CSV, and JSON formats.
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By default, Tune only logs the returned result dictionaries from the training function.
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If you need to log something lower level like model weights or gradients,
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see :ref:`Trainable Logging <trainable-logging>`.
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.. note::
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Tune's per-trial ``Logger`` classes have been deprecated. Use the ``LoggerCallback`` interface instead.
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.. currentmodule:: ray
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.. _logger-interface:
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LoggerCallback Interface (tune.logger.LoggerCallback)
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-----------------------------------------------------
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.. autosummary::
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:nosignatures:
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:toctree: doc/
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~tune.logger.LoggerCallback
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.. autosummary::
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:nosignatures:
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:toctree: doc/
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~tune.logger.LoggerCallback.log_trial_start
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~tune.logger.LoggerCallback.log_trial_restore
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~tune.logger.LoggerCallback.log_trial_save
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~tune.logger.LoggerCallback.log_trial_result
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~tune.logger.LoggerCallback.log_trial_end
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Tune Built-in Loggers
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---------------------
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.. autosummary::
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:nosignatures:
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:toctree: doc/
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tune.logger.JsonLoggerCallback
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tune.logger.CSVLoggerCallback
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tune.logger.TBXLoggerCallback
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MLFlow Integration
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------------------
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Tune also provides a logger for `MLflow <https://mlflow.org>`_.
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You can install MLflow via ``pip install mlflow``.
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See the :doc:`tutorial here </tune/examples/tune-mlflow>`.
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.. autosummary::
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:nosignatures:
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:toctree: doc/
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~air.integrations.mlflow.MLflowLoggerCallback
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~air.integrations.mlflow.setup_mlflow
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Wandb Integration
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-----------------
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Tune also provides a logger for `Weights & Biases <https://www.wandb.ai/>`_.
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You can install Wandb via ``pip install wandb``.
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See the :doc:`tutorial here </tune/examples/tune-wandb>`.
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.. autosummary::
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:nosignatures:
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:toctree: doc/
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~air.integrations.wandb.WandbLoggerCallback
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~air.integrations.wandb.setup_wandb
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Comet Integration
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------------------------------
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Tune also provides a logger for `Comet <https://www.comet.com/>`_.
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You can install Comet via ``pip install comet-ml``.
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See the :doc:`tutorial here </tune/examples/tune-comet>`.
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.. autosummary::
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:nosignatures:
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:toctree: doc/
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~air.integrations.comet.CometLoggerCallback
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Aim Integration
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---------------
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Tune also provides a logger for the `Aim <https://aimstack.io/>`_ experiment tracker.
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You can install Aim via ``pip install aim``.
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See the :doc:`tutorial here </tune/examples/tune-aim>`.
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.. autosummary::
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:nosignatures:
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:toctree: doc/
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~tune.logger.aim.AimLoggerCallback
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Other Integrations
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------------------
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Viskit
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~~~~~~
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Tune automatically integrates with `Viskit <https://github.com/vitchyr/viskit>`_ via the ``CSVLoggerCallback`` outputs.
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To use VisKit (you may have to install some dependencies), run:
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.. code-block:: bash
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$ git clone https://github.com/vitchyr/viskit.git
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$ python viskit/viskit/frontend.py ~/ray_results/my_experiment
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The non-relevant metrics (like timing stats) can be disabled on the left to show only the
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relevant ones (like accuracy, loss, etc.).
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.. image:: ../images/ray-tune-viskit.png
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