Metadata-Version: 2.1
Name: keras-radam
Version: 0.5.0
Summary: RAdam implemented in Keras
Home-page: https://github.com/CyberZHG/keras-radam
Author: CyberZHG
Author-email: CyberZHG@users.noreply.github.com
License: MIT
Description: # Keras RAdam
        
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        ![](https://img.shields.io/badge/keras-tensorflow-blue.svg)
        ![](https://img.shields.io/badge/keras-theano-blue.svg)
        ![](https://img.shields.io/badge/keras-tf.keras-blue.svg)
        ![](https://img.shields.io/badge/keras-tf.keras/eager-blue.svg)
        ![](https://img.shields.io/badge/keras-tf.keras/2.0_beta-blue.svg)
        
        \[[中文](https://github.com/CyberZHG/keras-radam/blob/master/README.zh-CN.md)|[English](https://github.com/CyberZHG/keras-radam/blob/master/README.md)\]
        
        Unofficial implementation of [RAdam](https://arxiv.org/pdf/1908.03265v1.pdf).
        
        ## Install
        
        ```bash
        pip install keras-rectified-adam
        ```
        
        ## Usage
        
        ```python
        import keras
        import numpy as np
        from keras_radam import RAdam
        
        # Build toy model with RAdam optimizer
        model = keras.models.Sequential()
        model.add(keras.layers.Dense(input_shape=(17,), units=3))
        model.compile(RAdam(), loss='mse')
        
        # Generate toy data
        x = np.random.standard_normal((4096 * 30, 17))
        w = np.random.standard_normal((17, 3))
        y = np.dot(x, w)
        
        # Fit
        model.fit(x, y, epochs=5)
        ```
        
        ### Use Warmup
        
        ```python
        from keras_radam import RAdam
        
        RAdam(total_steps=10000, warmup_proportion=0.1, min_lr=1e-5)
        ```
        
        ## Q & A
        
        ### About Correctness
        
        The optimizer produces similar losses and weights to the official optimizer after 500 steps.
        
        ### Use `tf.keras` or `tf-2.0`
        
        Add `TF_KERAS=1` to environment variables to use `tensorflow.python.keras`.
        
        ### Use `theano` Backend
        
        Add `KERAS_BACKEND=theano` to environment variables to enable `theano` backend.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
