From a94dc626b180414891e87aa94def76021d85180b Mon Sep 17 00:00:00 2001
From: Ilya Mironov <mironov@google.com>
Date: Fri, 17 May 2019 16:39:24 -0700
Subject: [PATCH] Specifying minimal TF version required (currently 1.13, due
 to dependency on the train module).

PiperOrigin-RevId: 248809713
---
 README.md        | 24 ++++++++++++------------
 requirements.txt |  4 ++--
 2 files changed, 14 insertions(+), 14 deletions(-)

diff --git a/README.md b/README.md
index cfb6ed3..6fd80a3 100644
--- a/README.md
+++ b/README.md
@@ -14,18 +14,18 @@ issues currently open.
 ### Dependencies
 
 This library uses [TensorFlow](https://www.tensorflow.org/) to define machine
-learning models. Therefore, installing TensorFlow is a pre-requisite. You can
-find instructions [here](https://www.tensorflow.org/install/). For better
-performance, it is also recommended to install TensorFlow with GPU support
-(detailed instructions on how to do this are available in the TensorFlow
+learning models. Therefore, installing TensorFlow (>= 1.13) is a pre-requisite.
+You can find instructions [here](https://www.tensorflow.org/install/). For
+better performance, it is also recommended to install TensorFlow with GPU
+support (detailed instructions on how to do this are available in the TensorFlow
 installation documentation).
 
 In addition to TensorFlow and its dependencies, other prerequisites are:
 
   * `scipy` >= 0.17
-  
+
   * `mpmath` (for testing)
-  
+
   * `tensorflow_datasets` (for the RNN tutorial `lm_dpsgd_tutorial.py` only)
 
 ### Installing TensorFlow Privacy
@@ -50,7 +50,7 @@ and then cloning your fork rather than cloning this repository directly.
 ## Contributing
 
 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
     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
 measure the privacy guarantees provided using analysis tools included in TF
 Privacy.
-  
+
 In addition, the
 `tutorials/` folder comes with scripts demonstrating how to use the library
 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
 tensorflow/models [repository](https://github.com/tensorflow/models/tree/master/research/differential_privacy)
-  
+
 ## Contacts
-  
+
 If you have any questions that cannot be addressed by raising an issue, feel
-free to contact: 
-  
+free to contact:
+
 * Galen Andrew (@galenmandrew)
 * Steve Chien (@schien1729)
 * Nicolas Papernot (@npapernot)
diff --git a/requirements.txt b/requirements.txt
index 1594174..cb596eb 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,3 @@
-tensorflow
+tensorflow>=1.13
 mpmath
-scipy
+scipy>=0.17