modelaverage

modelaverage is a pip package that calculates the average value of the same model, inspired by Average weights in keras models. I created it to train each mini-batch in one container as distributed computing environment, kubernetes.

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. type should be list

     averaged_model = average(['mnist1.h5', 'mnist2.h5',....])

   • return : input models of averaged weight

Example

Please see example.

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