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Adding contribution guidelines to TF Privacy
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tensorflow_privacy/privacy/membership_inference_attack/CONTRIBUTING.md
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# How to Contribute | ||
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We are happy to accept contributions to this project under the research folder. | ||
The research folder is intended for the attacks that are not yet generic enough | ||
to be included into the main library. | ||
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We are happy to accept contributions to the primary codebase, see below for more | ||
details. | ||
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Please follow these guidelines when sending us a pull request. | ||
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## Contributor License Agreement | ||
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Contributions to this project must be accompanied by a Contributor License | ||
Agreement. You (or your employer) retain the copyright to your contribution, | ||
this simply gives us permission to use and redistribute your contributions as | ||
part of the project. Head over to <https://cla.developers.google.com/> to see | ||
your current agreements on file or to sign a new one. | ||
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You generally only need to submit a CLA once, so if you've already submitted | ||
one (even if it was for a different project), you probably don't need to do it | ||
again. | ||
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## Community Guidelines | ||
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This project follows | ||
[Google's Open Source Community Guidelines](https://opensource.google.com/conduct/). | ||
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## Does my new feature belong here? | ||
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### Research folder | ||
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We use the following principles to guide what we add to our libraries. If your | ||
contribution doesn't align with these principles, we're likely to decline. | ||
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* **Novelty:** The code should provide new attacks to the library. We will not | ||
accept code that duplicates existing attacks. | ||
* **Appropriate context and explanation:** The code should contain a README.md | ||
file based on the provided template.This template should explain the code's functionality, and provide basic steps on how to use it. | ||
* **Experiment-driven:** The code should contain an runnable example or a colab (e.g. on a toy model such as MNIST or CIFAR-10). | ||
* **Quality requirements:** (1) The code should adhere to the | ||
[Google Python style guide](https://google.github.io/styleguide/pyguide). | ||
(2) The public API of the attack should have clear code documentation (expected inputs/outputs) | ||
(3) The code should have reasonable unit test coverage (>60%); | ||
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### Primary codebase | ||
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The primary codebase should include attacks that are of general interest and | ||
have a wide range of applications. For example, the standard membership | ||
inference test is applicable to virtually any classification model. | ||
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The code contributed to the primary codebase should have a production style API | ||
which is consistent with the API of other attacks. Most likely, Google and the | ||
contributing team will need to meet and discuss the API before starting the | ||
contribution. | ||
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If you're uncertain whether a planned contribution fits with these principles, | ||
[open an issue](https://github.com/tensorflow/privacy/issues/new) | ||
and describe what you want to add. We'll let you know whether it's something we | ||
want to include and will help you figure out the best way to implement it. | ||
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