From: Richard Wei <rxwei@google.com>
Date: Sun, 29 Apr 2018 06:51:28 +0000 (-0700)
Subject: Update the Swift for TensorFlow community page.
X-Git-Tag: upstream/v1.9.0_rc1~190^2^2~4
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=2e1f3efcb34380df1441660d9759b44bb07cf1cd;p=platform%2Fupstream%2Ftensorflow.git

Update the Swift for TensorFlow community page.

PiperOrigin-RevId: 194687897
---

diff --git a/tensorflow/docs_src/community/swift.md b/tensorflow/docs_src/community/swift.md
index f065b20..a7da189 100644
--- a/tensorflow/docs_src/community/swift.md
+++ b/tensorflow/docs_src/community/swift.md
@@ -1,18 +1,44 @@
-# Swift Community
+<p align="center">
+  <img src="../images/swift_tensorflow_logo.png">
+</p>
+
+# Swift for TensorFlow
 
 Welcome to the Swift for TensorFlow development community!
 
-Swift for TensorFlow is the result of first-principles thinking applied to
-machine learning frameworks and aims to take TensorFlow usability to new
-heights. Swift for TensorFlow is based on the belief that machine learning is
-important enough for first-class language and compiler support, and thus works
-very differently from normal language bindings.
-
-First-class language and compiler support allow us to innovate in areas that
-traditionally were out of bounds for machine learning libraries. Our
-programming model combines the performance of TensorFlow graphs with the
-flexibility and expressivity of Eager execution, while keeping a strong focus
-on improved usability at every level of the stack.
+Swift for TensorFlow is a new way to develop machine learning models. It
+gives you the power of
+[TensorFlow](https://www.tensorflow.org/programmers_guide/eager) directly
+integrated into the [Swift programming language](https://swift.org/about).
+With Swift, you can write the following imperative code, and Swift
+automatically turns it into **a single TensorFlow Graph** and runs it
+with the full performance of TensorFlow Sessions on CPU, GPU and
+[TPU](https://cloud.google.com/tpu/docs/tpus).
+
+```swift
+import TensorFlow
+
+var x = Tensor([[1, 2], [3, 4]])
+
+for i in 1...5 {
+  x += x ⊗ x
+}
+
+print(x)
+```
+
+Swift combines the flexibility of
+[Eager Execution](https://www.tensorflow.org/programmers_guide/eager) with the
+high performance of [Graphs and Sessions](https://www.tensorflow.org/programmers_guide/graphs).
+Behind the scenes, Swift analyzes your Tensor code and automatically builds
+graphs for you. Swift also catches type errors and shape mismatches before
+running your code, and has [Automatic Differentiation](https://en.wikipedia.org/wiki/Automatic_differentiation)
+built right in. We believe that machine learning tools are so important that
+they deserve **a first-class language and a compiler**.
+
+**Note:** Swift for TensorFlow is an early stage research project. It has been
+released to enable open source development and is not yet ready for general use
+by machine learning developers.
 
 ## Open Source