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########
Patching
########

.. glossary::

   patching
      To patch scikit-learn with |intelex| is to replace stock scikit-learn algorithms
      with their optimized versions provided by the extension. You can always :term:`undo the patch <unpatching>`.

      There are different ways to patch scikit-learn:

      .. include:: /patching/patching-options.rst

      .. seealso:: :ref:`get_started`

   global pathcing
      One of the patching options available in |intelex|.
      With global patching, you can patch all scikit-learn applications at once::

         python sklearnex.glob patch_sklearn
      
      .. seealso:: :ref:`global_patching`
   
   unpatching
      To undo the patch is to return to the use of original scikit-learn implementation and
      replace patched algorithms with the stock scikit-learn algorithms.
      Unpatching requires scikit-learn to be re-imported again:

      .. include:: /patching/undo-patch.rst

How it works
------------

The extension replaces the original estimators in scikit-learn modules with the optimized ones.
If the desired algorithm parameters are not supported by the |intelex|,
then the result of the original scikit-learn is returned.

.. seealso:: :ref:`verbose`