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IdiosyncraticDragon · Dec 1, 2018 · e0c17d0 · e0c17d0
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-# Optimization based Layer-wise Magnitude-based Pruning for DNN Compression Thank you for everyone who are intereted in our work.  
+# Optimization based Layer-wise Magnitude-based Pruning for DNN Compression 
+Thank you for everyone who are intereted in our work.  
 This repository is the implementation of OLMP. In experiments of LeNet-5 and LeNet-300-100, we have fixed the random seeds in python scripts for the purpose of reproducting the results shown in our paper. For AlexNet-Caltech, unfortunately, it has the dropout layers with the random seed inside Caffe framework which is the random seed we did not recorded during our experiments. Instead, We provide the compressed model of AlexNet-Caltech whoes results are reported in our paper. Users can also run the script of AlexNet-Caltech several times to reproduce a similar result compared to the one in our paper.
 
 This project is based on [Caffe](https://github.com/BVLC/caffe) and [Dynamic surgery](https://github.com/yiwenguo/Dynamic-Network-Surgery). Thanks to the authors of these two projects.