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TensorFlow > link > WILDML (2016/08/21) > protocol buffers > for serializing structured data

Last updated at Posted at 2016-11-05

Jupyter Notebookつきのドキュメント。

RNNs are used for sequential data that has inputs and/or outputs at multiple time steps. Tensorflow comes with a protocol buffer definition to deal with such data: tf.SequenceExample.

上記のリンク先から
https://developers.google.com/protocol-buffers/

Protocol buffers are Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data

上記のWILDMLさんの記事にてprotocol buffersを使う利点が4つ紹介されている。

but it comes with a few benefits that are worth it:

以降

気になるのはReusabilityとSeparation of data preprocessing and model code.
RNNを使わないとしても(回帰のネットをするにしても)、この機能は便利かもしれない。

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