Metadata-Version: 2.1
Name: modelaverage
Version: 1.0.1
Summary: tf-keras, make the average of model weight in same models
Home-page: https://github.com/graykode/modelaverage
Author: Tae Hwan Jung(@graykode)
Author-email: nlkey2022@gmail.com
License: MIT
Description: ## modelaverage
        
        <p align="center">
            <img width="100" src="https://upload.wikimedia.org/wikipedia/commons/thumb/1/11/TensorFlowLogo.svg/225px-TensorFlowLogo.svg.png" />
            <img width="100" src="https://keras.io/img/keras-logo-small-wb.png" />
        </p>
        `modelaverage` is a pip package which make the average weight of model weight in `same models`, inspired by [Average weights in keras models](https://stackoverflow.com/questions/48212110/average-weights-in-keras-models). I created this pip package to use distributed computing environment like `kubernetes`.
        
        ![](average.jpg)
        
        ## Usage
        
        1. `pip install modelaverage` or `git clone https://github.com/graykode/modelaverage && python setup.py install`
        2. using function `average(modellist)`
           - modellist : list of model file names.
           - return : averaged weight model
        
        
        
        ## Example
        
        Please see example
        
        ```python
        import tensorflow as tf
        from modelaverage import average
        
        modellist = ['models/mnist1.h5', 'models/mnist2.h5', 'models/mnist3.h5', 'models/mnist4.h5', 'models/mnist5.h5',
                     'models/mnist6.h5', 'models/mnist7.h5', 'models/mnist8.h5', 'models/mnist9.h5']
        
        averaged_model = average(modellist)
        
        for w in averaged_model.get_weights():
            print(w.shape)
        ```
        
        
        
        ## Author
        
        - Name : Tae Hwan Jung(@graykode)
        - Email : nlkey2022@gmail.com
Keywords: pytorch model summary model.summary()
Platform: UNKNOWN
Description-Content-Type: text/markdown
