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Specifying minimal TF version required (currently 1.13, due to dependency on the train module).

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Ilya Mironov 2019-05-17 16:39:24 -07:00 committed by A. Unique TensorFlower
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24
README.md
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@ -14,18 +14,18 @@ issues currently open.
### Dependencies ### Dependencies
This library uses [TensorFlow](https://www.tensorflow.org/) to define machine This library uses [TensorFlow](https://www.tensorflow.org/) to define machine
learning models. Therefore, installing TensorFlow is a pre-requisite. You can learning models. Therefore, installing TensorFlow (>= 1.13) is a pre-requisite.
find instructions [here](https://www.tensorflow.org/install/). For better You can find instructions [here](https://www.tensorflow.org/install/). For
performance, it is also recommended to install TensorFlow with GPU support better performance, it is also recommended to install TensorFlow with GPU
(detailed instructions on how to do this are available in the TensorFlow support (detailed instructions on how to do this are available in the TensorFlow
installation documentation). installation documentation).
In addition to TensorFlow and its dependencies, other prerequisites are: In addition to TensorFlow and its dependencies, other prerequisites are:
* `scipy` >= 0.17 * `scipy` >= 0.17
* `mpmath` (for testing) * `mpmath` (for testing)
* `tensorflow_datasets` (for the RNN tutorial `lm_dpsgd_tutorial.py` only) * `tensorflow_datasets` (for the RNN tutorial `lm_dpsgd_tutorial.py` only)
### Installing TensorFlow Privacy ### Installing TensorFlow Privacy
@ -50,7 +50,7 @@ and then cloning your fork rather than cloning this repository directly.
## Contributing ## Contributing
Contributions are welcomed! Bug fixes and new features can be initiated through Contributions are welcomed! Bug fixes and new features can be initiated through
Github pull requests. To speed the code review process, we ask that: GitHub pull requests. To speed the code review process, we ask that:
* When making code contributions to TensorFlow Privacy, you follow the `PEP8 * When making code contributions to TensorFlow Privacy, you follow the `PEP8
with two spaces` coding style (the same as the one used by TensorFlow) in with two spaces` coding style (the same as the one used by TensorFlow) in
@ -73,7 +73,7 @@ TensorFlow (TF) Privacy. You will also learn how to tune the parameters
introduced by differentially private optimization and how to introduced by differentially private optimization and how to
measure the privacy guarantees provided using analysis tools included in TF measure the privacy guarantees provided using analysis tools included in TF
Privacy. Privacy.
In addition, the In addition, the
`tutorials/` folder comes with scripts demonstrating how to use the library `tutorials/` folder comes with scripts demonstrating how to use the library
features. The list of tutorials is described in the README included in the features. The list of tutorials is described in the README included in the
@ -94,12 +94,12 @@ directory, but rather intended as a convenient archive.
The content of this repository supersedes the following existing folder in the The content of this repository supersedes the following existing folder in the
tensorflow/models [repository](https://github.com/tensorflow/models/tree/master/research/differential_privacy) tensorflow/models [repository](https://github.com/tensorflow/models/tree/master/research/differential_privacy)
## Contacts ## Contacts
If you have any questions that cannot be addressed by raising an issue, feel If you have any questions that cannot be addressed by raising an issue, feel
free to contact: free to contact:
* Galen Andrew (@galenmandrew) * Galen Andrew (@galenmandrew)
* Steve Chien (@schien1729) * Steve Chien (@schien1729)
* Nicolas Papernot (@npapernot) * Nicolas Papernot (@npapernot)

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requirements.txt
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@ -1,3 +1,3 @@
tensorflow tensorflow>=1.13
mpmath mpmath
scipy scipy>=0.17