.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/visualkeras_CNN/plot_autoencoder.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_visualkeras_CNN_plot_autoencoder.py>`
        to download the full example code. or to run this example in your browser via JupyterLite or Binder

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

.. _sphx_glr_auto_examples_visualkeras_CNN_plot_autoencoder.py:


visualkeras autoencoder example
==========================================

An example showing the :py:func:`~scikitplot.visualkeras` function
used by a :py:class:`~tensorflow.keras.Model` model.

.. GENERATED FROM PYTHON SOURCE LINES 8-57

.. code-block:: Python

    # Authors: The scikit-plots developers
    # SPDX-License-Identifier: BSD-3-Clause

    # Force garbage collection
    import gc; gc.collect()
    import tensorflow as tf
    # Clear any session to reset the state of TensorFlow/Keras
    tf.keras.backend.clear_session()

    # encoder Model
    encoder_input = tf.keras.Input(shape=(28, 28, 1), name='img')
    x = tf.keras.layers.Conv2D(16, 3, activation='relu')(encoder_input)
    x = tf.keras.layers.Conv2D(32, 3, activation='relu')(x)
    x = tf.keras.layers.MaxPooling2D(3)(x)
    x = tf.keras.layers.Conv2D(32, 3, activation='relu')(x)
    x = tf.keras.layers.Conv2D(16, 3, activation='relu')(x)
    encoder_output = tf.keras.layers.GlobalMaxPooling2D()(x)
    encoder = tf.keras.Model(encoder_input, encoder_output, name='encoder')

    # autoencoder Model
    x = tf.keras.layers.Reshape((4, 4, 1))(encoder_output)
    x = tf.keras.layers.Conv2DTranspose(16, 3, activation='relu')(x)
    x = tf.keras.layers.Conv2DTranspose(32, 3, activation='relu')(x)
    x = tf.keras.layers.UpSampling2D(3)(x)
    x = tf.keras.layers.Conv2DTranspose(16, 3, activation='relu')(x)
    decoder_output = tf.keras.layers.Conv2DTranspose(1, 3, activation='relu')(x)
    autoencoder = tf.keras.Model(encoder_input, decoder_output, name='autoencoder')

    from scikitplot import visualkeras

    img_encoder = visualkeras.layered_view(
      encoder,
      to_file='../result_images/encoder.png'
    )
    img_autoencoder = visualkeras.layered_view(
      autoencoder,
      to_file='../result_images/autoencoder.png'
    )
    try:
        import matplotlib.pyplot as plt
        plt.imshow(img_encoder)
        plt.axis('off')
        plt.show()
        plt.imshow(img_autoencoder)
        plt.axis('off')
        plt.show()
    except:
        pass




.. image-sg:: /auto_examples/visualkeras_CNN/images/sphx_glr_plot_autoencoder_001.png
   :alt: plot autoencoder
   :srcset: /auto_examples/visualkeras_CNN/images/sphx_glr_plot_autoencoder_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 58-65

.. tags::

   model-type: classification
   model-workflow: model building
   plot-type: visualkeras
   domain: neural network
   level: beginner
   purpose: showcase


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

   **Total running time of the script:** (0 minutes 0.718 seconds)


.. _sphx_glr_download_auto_examples_visualkeras_CNN_plot_autoencoder.py:

.. only:: html

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

    .. container:: binder-badge

      .. image:: images/binder_badge_logo.svg
        :target: https://mybinder.org/v2/gh/scikit-plots/scikit-plots/0.4.X?urlpath=lab/tree/notebooks/auto_examples/visualkeras_CNN/plot_autoencoder.ipynb
        :alt: Launch binder
        :width: 150 px

    .. container:: lite-badge

      .. image:: images/jupyterlite_badge_logo.svg
        :target: ../../lite/lab/index.html?path=auto_examples/visualkeras_CNN/plot_autoencoder.ipynb
        :alt: Launch JupyterLite
        :width: 150 px

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

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

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

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

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

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


.. include:: plot_autoencoder.recommendations


.. only:: html

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

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