2020-04-21 11:19:42 -04:00
|
|
|
---
|
|
|
|
id: 5e8f2f13c4cdbe86b5c72da0
|
2020-04-24 05:52:42 -05:00
|
|
|
title: 'Natural Language Processing With RNNs: Create a Play Generator'
|
2020-04-21 11:19:42 -04:00
|
|
|
challengeType: 11
|
|
|
|
videoId: j5xsxjq_Xk8
|
|
|
|
---
|
|
|
|
|
|
|
|
## Description
|
|
|
|
<section id='description'>
|
|
|
|
</section>
|
|
|
|
|
|
|
|
## Tests
|
|
|
|
<section id='tests'>
|
|
|
|
|
|
|
|
```yml
|
|
|
|
question:
|
2020-05-28 22:40:36 +09:00
|
|
|
text: |
|
|
|
|
Fill in the blanks below to create the training examples for the RNN:
|
|
|
|
|
|
|
|
```py
|
|
|
|
char_dataset = tf.data.__A__.__B__(text_as_int)
|
|
|
|
```
|
|
|
|
|
2020-04-21 11:19:42 -04:00
|
|
|
answers:
|
2020-05-28 22:40:36 +09:00
|
|
|
- |
|
|
|
|
A: `DataSet`
|
|
|
|
|
|
|
|
B: `from_tensor_slices`
|
|
|
|
- |
|
|
|
|
A: `data`
|
|
|
|
|
|
|
|
B: `from_tensors`
|
|
|
|
- |
|
|
|
|
A: `DataSet`
|
|
|
|
|
|
|
|
B: `from_generator`
|
|
|
|
solution: 1
|
2020-04-21 11:19:42 -04:00
|
|
|
```
|
|
|
|
|
|
|
|
</section>
|
|
|
|
|