Metadata-Version: 1.1
Name: keras-targeted-dropout
Version: 0.2.0
Summary: Targeted dropout implemented in Keras
Home-page: https://github.com/CyberZHG/keras-targeted-dropout
Author: CyberZHG
Author-email: CyberZHG@gmail.com
License: MIT
Description: 
        Keras Targeted Dropout
        ======================
        
        
        .. image:: https://travis-ci.org/CyberZHG/keras-targeted-dropout.svg
           :target: https://travis-ci.org/CyberZHG/keras-targeted-dropout
           :alt: Travis
        
        
        .. image:: https://coveralls.io/repos/github/CyberZHG/keras-targeted-dropout/badge.svg?branch=master
           :target: https://coveralls.io/github/CyberZHG/keras-targeted-dropout
           :alt: Coverage
        
        
        Implementation of `Targeted Dropout <https://openreview.net/pdf?id=HkghWScuoQ>`_ with tensorflow backend.
        
        Install
        -------
        
        .. code-block:: bash
        
           pip install keras-targeted-dropout
        
        Usage
        -----
        
        .. code-block:: python
        
           import keras
           from keras_targeted_dropout import TargetedDropout
        
           model = keras.models.Sequential()
           model.add(TargetedDropout(input_shape=(None, None), drop_rate=0.4, target_rate=0.4))
           model.compile(optimizer='adam', loss='mse')
           model.summary()
        
        
        * ``drop_rate``\ : Dropout rate for each pixel.
        * ``target_rate``\ : The proportion of bottom weights selected as candidates per channel.
        
        The final dropout rate will be ``drop_rate`` times ``target_rate``.
        
        See `Fashion MNIST demo <https://github.com/CyberZHG/keras-targeted-dropout/blob/master/demo/mnist.py>`_.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
