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2 changes: 1 addition & 1 deletion doc/conf.py
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Expand Up @@ -49,7 +49,7 @@
autosummary_generate = True
numpydoc_show_class_members = False

autodoc_default_flags = ["members", "inherited-members"]
autodoc_default_options = {"members": True, "inherited-members": True}

# Add any paths that contain templates here, relative to this directory.
templates_path = ["_templates"]
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2 changes: 1 addition & 1 deletion doc/index.rst
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Expand Up @@ -38,7 +38,7 @@ Example
# Publish the experiment on OpenML (optional, requires an API key.
# You can get your own API key by signing up to OpenML.org)
run.publish()
print(f'View the run online: {openml.config.server}/run/{run.run_id}')
print(f'View the run online: {run.openml_url}')

You can find more examples in our `examples gallery <examples/index.html>`_.

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15 changes: 14 additions & 1 deletion doc/progress.rst
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Expand Up @@ -6,7 +6,20 @@
Changelog
=========

0.11.1
0.12.1
~~~~~~

* ADD #895/#1038: Measure runtimes of scikit-learn runs also for models which are parallelized
via the joblib.
* DOC #1050: Refer to the webpage instead of the XML file in the main example.
* DOC #1051: Document existing extensions to OpenML-Python besides the shipped scikit-learn
extension.
* FIX #1035: Render class attributes and methods again.
* FIX #1042: Fixes a rare concurrency issue with OpenML-Python and joblib which caused the joblib
worker pool to fail.
* FIX #1053: Fixes a bug which could prevent importing the package in a docker container.

0.12.0
~~~~~~
* ADD #964: Validate ``ignore_attribute``, ``default_target_attribute``, ``row_id_attribute`` are set to attributes that exist on the dataset when calling ``create_dataset``.
* ADD #979: Dataset features and qualities are now also cached in pickle format.
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16 changes: 14 additions & 2 deletions doc/usage.rst
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Expand Up @@ -145,10 +145,22 @@ obtained on. Learn how to share your datasets in the following tutorial:

* `Upload a dataset <examples/30_extended/create_upload_tutorial.html>`_

~~~~~~~~~~~~~~~~~~~~~~~
***********************
Extending OpenML-Python
~~~~~~~~~~~~~~~~~~~~~~~
***********************

OpenML-Python provides an extension interface to connect other machine learning libraries than
scikit-learn to OpenML. Please check the :ref:`api_extensions` and use the
scikit-learn extension in :class:`openml.extensions.sklearn.SklearnExtension` as a starting point.

Runtime measurement is incorporated in the OpenML sklearn-extension. Example usage and potential
usage for Hyperparameter Optimisation can be found in the example tutorial:
`HPO using OpenML <examples/30_extended/fetch_runtimes.html>`_


Here is a list of currently maintained OpenML extensions:

* `openml-keras <https://github.com/openml/openml-keras>`_
* `openml-pytorch <https://github.com/openml/openml-pytorch>`_
* `openml-tensorflow(for tensorflow 2+) <https://github.com/openml/openml-tensorflow>`_

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