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Toshihiko Yanase
2023-11-10 15:02:48 +09:00
parent 985b301f67
commit da70fbe2fa
1 changed files with 2 additions and 2 deletions
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docs/tutorials/preferential-optimization.rst
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@@ -99,7 +99,7 @@ enabling the Optuna Dashboard to display images on the evaluation feedback page.
register_preference_feedback_component(study, "artifact", user_attr_key)
Following this, we create a loop that continuously checks if new trials should be generated, awaiting human evaluation if not.
Within the while loop, new trials are generated if the condition :meth:`~optuna_dashboard.preferential.PreferentialStudy.should_generate` returns ``True``.
Within the while loop, new trials are generated if the condition :meth:`~optuna_dashboard.preferential.PreferentialStudy.should_generate` returns ``True``.
For each trial, RGB values are sampled, an image is generated with these values, saved temporarily.
Then the image is uploaded to the artifact store, and finally, the ``artifact_id`` is stored to the key, which is specified via :func:`~optuna_dashboard.register_preference_feedback_component`.
@@ -127,4 +127,4 @@ Then the image is uploaded to the artifact store, and finally, the ``artifact_id
artifact_id = upload_artifact(trial, image_path, artifact_store)
trial.set_user_attr(user_attr_key, artifact_id)
.. _generator.py: https://github.com/optuna/optuna-dashboard/blob/main/examples/preferential-optimization/generator.py
.. _generator.py: https://github.com/optuna/optuna-examples/blob/main/dashboard/preferential-optimization/generator.py