Metadata-Version: 2.1
Name: keras-adabound
Version: 0.6.0
Summary: AdaBound optimizer in Keras
Home-page: https://github.com/CyberZHG/keras-adabound
Author: CyberZHG
Author-email: CyberZHG@gmail.com
License: MIT
Description: # Keras AdaBound
        
        [![Travis](https://travis-ci.org/CyberZHG/keras-adabound.svg)](https://travis-ci.org/CyberZHG/keras-adabound)
        [![Coverage](https://coveralls.io/repos/github/CyberZHG/keras-adabound/badge.svg?branch=master)](https://coveralls.io/github/CyberZHG/keras-adabound)
        
        [AdaBound](https://github.com/Luolc/AdaBound) optimizer in Keras.
        
        ## Install
        
        ```bash
        pip install keras-adabound
        ```
        
        ## Usage
        
        ### Use the optimizer
        
        ```python
        from keras_adabound import AdaBound
        
        model.compile(optimizer=AdaBound(lr=1e-3, final_lr=0.1), loss=model_loss)
        ```
        
        ### Load with custom objects
        
        ```python
        from keras_adabound import AdaBound
        
        model = keras.models.load_model(model_path, custom_objects={'AdaBound': AdaBound})
        ```
        
        ### About weight decay
        
        The optimizer does not have an argument named `weight_decay` (as in the official repo) since it can be done by adding L2 regularizers to weights:
        
        ```python
        import keras
        
        regularizer = keras.regularizers.l2(WEIGHT_DECAY / 2)
        for layer in model.layers:
            for attr in ['kernel_regularizer', 'bias_regularizer']:
                if hasattr(layer, attr) and layer.trainable:
                    setattr(layer, attr, regularizer)
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
