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hugovk / char-rnn-tensorflow / 39 / 2
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master: 93%

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DEFAULT BRANCH: master
Ran 12 Mar 2017 07:57AM UTC
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12 Mar 2017 12:58AM UTC coverage: 92.72% (-1.0%) from 93.697%
39.2

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Split dropout into input and output parameters

Usage example:
```
python train.py --input_keep_prob=0.8 --output_keep_prob=0.5
```

Useing dropout will likely slow down training and
may not prevent overfitting. For more details read:
https://www.cs.toronto.edu/~hinton/absps/JMLRdropout.pdf

Any code review here would be welcome!

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