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Shan Yi 7 years ago committed by GitHub
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@ -5,7 +5,7 @@ This document describes the RNN (Recurrent Neural Network) operator and how it i
## RNN Algorithm Implementation
<p align="center">
<img src="./images/rnn.jpg"/>
<img src="./rnn.jpg"/>
</p>
The above diagram shows an RNN unrolled into a full network.
@ -22,7 +22,7 @@ There are several important concepts here:
There could be local variables defined in each step-net. PaddlePaddle runtime realizes these variables in *step-scopes* which are created for each step.
<p align="center">
<img src="./images/rnn.png"/><br/>
<img src="./rnn.png"/><br/>
Figure 2 illustrates the RNN's data flow
</p>
@ -93,7 +93,7 @@ For example, we could have a 2-level RNN, where the top level corresponds to par
The following figure illustrates feeding in text into the lower level, one sentence at a step, and the feeding in step outputs to the top level. The final top level output is about the whole text.
<p align="center">
<img src="./images/2_level_rnn.png"/>
<img src="./2_level_rnn.png"/>
</p>
```python
@ -149,5 +149,5 @@ If the `output_all_steps` is set to False, it will only output the final time st
<p align="center">
<img src="images/rnn_2level_data.png"/>
<img src="rnn_2level_data.png"/>
</p>

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