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fchollet 2015-12-05 19:32:14 -08:00
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2
CONTRIBUTING.md
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@ -36,7 +36,7 @@ We love pull requests. Here's a quick guide:
1. If your PR introduces a change in functionality, make sure you start by opening an issue to discuss whether the change should be made, and how to handle it. This will save you from having your PR closed down the road! Of course, if your PR is a simple bug fix, you don't need to do that.
2. Write the code. This is the hard part! We use PEP8 syntax conventions, but we aren't dogmatic when it comes to line length. Make sure your lines stay reasonably sized, though.
2. Write the code. This is the hard part! We use PEP8 syntax conventions, but we aren't dogmatic when it comes to line length. Make sure your lines stay reasonably sized, though. To make your life easier, we recommend installing a PEP8 linter.
3. Make sure any new function or class you introduce has proper docstrings. Make sure any code you touch still has up-to-date docstrings and documentation.

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README.md
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@ -145,20 +145,7 @@ By default, Keras will use Theano as its tensor manipulation library. [Follow th
You can ask questions and join the development discussion on the [Keras Google group](https://groups.google.com/forum/#!forum/keras-users).
------------------
## Contribution Guidelines
Keras welcomes all contributions from the community.
- Keep a pragmatic mindset and avoid bloat. Only add to the source if that is the only path forward.
- New features should be documented. Make sure you update the documentation along with your Pull Request.
- Any new function or class should have a proper docstring.
- The documentation for every new feature should include a usage example in the form of a code snippet.
- All changes should be tested. Make sure any new feature you add has a corresponding unit test.
- Please no Pull Requests about coding style.
- Even if you don't contribute to the Keras source code, if you have an application of Keras that is concise and powerful, please consider adding it to our collection of [examples](https://github.com/fchollet/keras/tree/master/examples).
You can also post bug reports and feature requests in [Github issues](https://github.com/fchollet/keras/issues). Make sure to read [our guidelines](https://github.com/fchollet/keras/blob/master/CONTRIBUTING.md) first.
------------------

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docs/sources/index.md
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@ -108,7 +108,7 @@ Keras uses the following dependencies:
- HDF5 and h5py (optional, required if you use model saving/loading functions)
- Optional but recommended if you use CNNs: cuDNN.
When using the Theano backend:
*When using the Theano backend:*
- Theano
- [See installation instructions](http://deeplearning.net/software/theano/install.html#install).
@ -117,11 +117,11 @@ When using the Theano backend:
sudo pip install git+git://github.com/Theano/Theano.git
```
When using the TensorFlow backend:
*When using the TensorFlow backend:*
- TensorFlow
- [See installation instructions](https://github.com/tensorflow/tensorflow#download-and-setup).
To install, `cd` to the Keras folder and run the install command:
To install Keras, `cd` to the Keras folder and run the install command:
```
sudo python setup.py install
```
@ -145,20 +145,7 @@ By default, Keras will use Theano as its tensor manipulation library. [Follow th
You can ask questions and join the development discussion on the [Keras Google group](https://groups.google.com/forum/#!forum/keras-users).
------------------
## Contribution Guidelines
Keras welcomes all contributions from the community.
- Keep a pragmatic mindset and avoid bloat. Only add to the source if that is the only path forward.
- New features should be documented. Make sure you update the documentation along with your Pull Request.
- Any new function or class should have a proper docstring.
- The documentation for every new feature should include a usage example in the form of a code snippet.
- All changes should be tested. Make sure any new feature you add has a corresponding unit test.
- Please no Pull Requests about coding style.
- Even if you don't contribute to the Keras source code, if you have an application of Keras that is concise and powerful, please consider adding it to our collection of [examples](https://github.com/fchollet/keras/tree/master/examples).
You can also post bug reports and feature requests in [Github issues](https://github.com/fchollet/keras/issues). Make sure to read [our guidelines](https://github.com/fchollet/keras/blob/master/CONTRIBUTING.md) first.
------------------