lizq66 / DEKM-Pytorch

A convenient "DEKM" implemented in PyTorch

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Overview

Result (MNIST)

  • Training Result
    Average accuracy of training data can reach over 85%, maximum can reach over 92%.
    model weight is at ./weight

  • Test Result

Usage

python train.py -pre_epoch 15 -epoch 10 -k 10
  • if your cuda memory is not enough, you should use less training data:
    add the command parameter -take, -take 0.8 will only use 80% training data.
python train.py -pre_epoch 15 -epoch 10 -k 10 -take 0.8

Note

This repository is mainly for academic purposes.

About

A convenient "DEKM" implemented in PyTorch

License:GNU General Public License v3.0


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Language:Python 100.0%