.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/deep/plot_divergence.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_deep_plot_divergence.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_deep_plot_divergence.py:


Divergence domain adaptation methods.
==========================================

This example illustrates the DeepCoral method from [1]
on a simple image classification task.

.. [1]  Baochen Sun and Kate Saenko. Deep coral:
        Correlation alignment for deep domain
        adaptation. In ECCV Workshops, 2016.

.. GENERATED FROM PYTHON SOURCE LINES 13-18

.. code-block:: Python

    # Author: Théo Gnassounou
    #
    # License: BSD 3-Clause
    # sphinx_gallery_thumbnail_number = 4








.. GENERATED FROM PYTHON SOURCE LINES 19-26

.. code-block:: Python

    from skorch import NeuralNetClassifier
    from torch import nn

    from skada.datasets import load_mnist_usps
    from skada.deep import DeepCoral
    from skada.deep.modules import MNISTtoUSPSNet








.. GENERATED FROM PYTHON SOURCE LINES 27-29

Load the image datasets
----------------------------------------------------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 29-34

.. code-block:: Python


    dataset = load_mnist_usps(n_classes=2, n_samples=0.5, return_dataset=True)
    X, y, sample_domain = dataset.pack_train(as_sources=["mnist"], as_targets=["usps"])
    X_test, y_test, sample_domain_test = dataset.pack_test(as_targets=["usps"])





.. rst-class:: sphx-glr-script-out

 .. code-block:: none


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      mnist_target = torch.tensor(mnist_dataset.targets)

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.. GENERATED FROM PYTHON SOURCE LINES 35-37

Train a classic model
----------------------------------------------------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 37-48

.. code-block:: Python

    model = NeuralNetClassifier(
        MNISTtoUSPSNet(),
        criterion=nn.CrossEntropyLoss(),
        batch_size=128,
        max_epochs=5,
        train_split=False,
        lr=1e-2,
    )
    model.fit(X[sample_domain > 0], y[sample_domain > 0])
    model.score(X_test, y=y_test)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

      epoch    train_loss     dur
    -------  ------------  ------
          1        1.6348  3.6962
          2        0.3176  3.4033
          3        0.1082  3.2970
          4        0.0643  3.3030
          5        0.0456  3.4945

    0.8842443729903537



.. GENERATED FROM PYTHON SOURCE LINES 49-51

Train a DeepCoral model
----------------------------------------------------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 51-62

.. code-block:: Python

    model = DeepCoral(
        MNISTtoUSPSNet(),
        layer_name="fc1",
        batch_size=128,
        max_epochs=5,
        train_split=False,
        reg=1,
        lr=1e-2,
    )
    model.fit(X, y, sample_domain=sample_domain)
    model.score(X_test, y_test, sample_domain=sample_domain_test)




.. rst-class:: sphx-glr-script-out

 .. code-block:: none

      epoch    train_loss     dur
    -------  ------------  ------
          1        1.4456  7.0768
          2        0.2629  6.5027
          3        0.1114  6.7957
          4        0.0737  6.6992
          5        0.0648  7.1999

    0.9517684887459807




.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (1 minutes 0.276 seconds)


.. _sphx_glr_download_auto_examples_deep_plot_divergence.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_divergence.ipynb <plot_divergence.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_divergence.py <plot_divergence.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_divergence.zip <plot_divergence.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_