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All Projects → hccho2 → Tensorflow-RNN-Tutorial

hccho2 / Tensorflow-RNN-Tutorial

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Tensorflow RNN Tutorial

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Tensorflow RNN-tutorial

-1. Tensorflow RNN Basic of Basic

여기서는 Tensorflow에서 RNN 모델에 대한 공부를 시작할 때 배우게 되는 dynamic_rnn에 대해서 알아본다.

  • dynamic_rnn은 Seq2Seq(Encoder-Decoder)모델을 배우기 전에 먼저 알아야 할 기본적인 RNN 모델 API이다.

0. Basic RNN Model

Tensorflow의 다음과 같은 API를 사용하여 기본적인 RNN 모델의 작동 원리를 알 수 있다.

  • dynamic_decode를 사용하여 Tensorflow RNN모델 사용법에 관해 알아본다.
  • BasicRNNCell, BasicLSTMCell, GRUCell
  • TrainingHelper, GreedyEmbeddingHelper
  • BasicDecoder
  • dynamic_decode

1. User Defined RNNWrapper

사용자 정의 RNN Wrapper를 만드는 방법에 대하여 알아본다.

  • RNNCell을 상속받아 사용자 정의 RNN Wrapper class를 정의한다.
  • 여기서 만드는 RNN Wrapper는 BasicRNNCell을 대체할 수 있다.

2. User Defined Helper

주로 사용하는 TrainingHelper, GreedyEmbeddingHelper, SampleEmbeddingHelper를 대신할 수 있는 사용자 정의 Helper를 만들어 보자.

  • Tacotron과 같은 모델에서는 RNN decoder를 구현하려면 사용자 정의 Helper가 반드시 필요하다.

3. User Defined Decoder

BasicDecoder를 대체할 수 있는 사용자 정의 Decoder를 만들어 보자.

4. Attention with Tensorflow

  • Bahdanau Attention, Luong Attention이 Tensorflow내에서 어떻게 작동하는지에 대하여 알아 보자.
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