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NNC based keras turorial

description

これは、Sony Neural Network Console(NNC)に実装されてる,

  • RNN: elmannet mnist
  • tutorial.recurrent_neural_networks.elman_net
  • CNN: LeNet mnist
  • tutorial.binary_networks.binary_net_mnist_LeNet

をkerasで実装した直したものである。

ここで得られることとしては、

  • NNCのデータセットの転用方法
  • NNC側で体験したものを再実装する力
  • kerasにおいての実装から計測方法
  • CSVを書き換えることで4or9だけではなく自分で1or9などを実装できる

NNCを利用して雰囲気を掴み、それを実装することで理解を深めるのに利用できると思います。

require

  • pipenv installed
  • python3 installed
  • keras + backend plaidml

prepare

pipenv install

# exec subshell
pipenv shell 

# keras backend setup
plaidml-setup

# make dataset
cd tools
python create_mnist_csv.py

run example

RNN

# 4 or 9 binary Category 
python main.py rnn_bi

# 0-9 ten Category 
python main.py rnn_cat

CNN

# 0-9 ten Category 
python main.py rnn_cat

参考資料と謝辞

最後ではあるが、NNCを通じてデータを公開してくれたソニー株式会社様、まとめる機会をくれた東北学院大の担当教員たちに感謝。

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