Update TF Lite subsite

PiperOrigin-RevId: 213737482

18 files changed, 227 insertions, 81 deletions

diff --git a/tensorflow/contrib/lite/g3doc/_book.yaml b/tensorflow/contrib/lite/g3doc/_book.yaml
index 1dffe30790..6f56e3139f 100644
--- a/tensorflow/contrib/lite/g3doc/_book.yaml
+++ b/tensorflow/contrib/lite/g3doc/_book.yaml
@@ -14,46 +14,49 @@ upper_tabs:
     - name: Guide
       contents:
       - title: Overview
-        path: /mobile/overview
-      - title: Developer Guide
-        path: /mobile/devguide
-      - title: Android Demo App
-        path: /mobile/demo_android
-      - title: iOS Demo App
-        path: /mobile/demo_ios
+        path: /lite/overview
+      - title: Developer guide
+        path: /lite/devguide
+      - title: Android demo app
+        path: /lite/demo_android
+      - title: iOS demo app
+        path: /lite/demo_ios
       - title: Performance
-        path: /mobile/performance
+        path: /lite/performance
       - break: True
       - title: TensorFlow Lite APIs
-        path: /mobile/apis
+        path: /lite/apis
       - title: Custom operators
-        path: /mobile/custom_operators
-      - title: TensorFlow Lite Ops Versioning
-        path: /mobile/ops_versioning
-      - title: TensorFlow Lite Compatibility Guide
-        path: /mobile/tf_ops_compatibility
-      - title: List of Hosted Models
-        path: /mobile/models
+        path: /lite/custom_operators
+      - title: TensorFlow Lite ops versioning
+        path: /lite/ops_versioning
+      - title: TensorFlow Lite compatibility guide
+        path: /lite/tf_ops_compatibility
+      - title: List of hosted models
+        path: /lite/models
       - title: TensorFlow Lite for iOS
-        path: /mobile/ios
+        path: /lite/ios
       - title: TensorFlow Lite for Raspberry Pi
-        path: /mobile/rpi
+        path: /lite/rpi
 
-      - heading: TF Mobile
+      - title: TF Mobile
+        style: accordion
         status: deprecated
-      - title: Overview
-        path: /mobile/tfmobile/
-      - title: Building TensorFlow on Android
-        path: /mobile/tfmobile/android_build
-      - title: Building TensorFlow on IOS
-        path: /mobile/tfmobile/ios_build
-      - title: Integrating TensorFlow libraries
-        path: /mobile/tfmobile/linking_libs
-      - title: Preparing models for mobile deployment
-        path: /mobile/tfmobile/prepare_models
-      - title: Optimizing for mobile
-        path: /mobile/tfmobile/optimizing
+        section:
+        - title: Overview
+          path: /lite/tfmobile/
+        - title: Building TensorFlow on Android
+          path: /lite/tfmobile/android_build
+        - title: Building TensorFlow on IOS
+          path: /lite/tfmobile/ios_build
+        - title: Integrating TensorFlow libraries
+          path: /lite/tfmobile/linking_libs
+        - title: Preparing models for mobile deployment
+          path: /lite/tfmobile/prepare_models
+        - title: Optimizing for mobile
+          path: /lite/tfmobile/optimizing
 
     - name: API
       contents:
-      - include: /mobile/api_docs/python/_toc.yaml
+      - title: API
+        path: /api_docs/python/tf/contrib/lite
diff --git a/tensorflow/contrib/lite/g3doc/_index.yaml b/tensorflow/contrib/lite/g3doc/_index.yaml
index b3f21e21ac..bc66cc5dc1 100644
--- a/tensorflow/contrib/lite/g3doc/_index.yaml
+++ b/tensorflow/contrib/lite/g3doc/_index.yaml
@@ -1,60 +1,209 @@
-book_path: /mobile/_book.yaml
-project_path: /mobile/_project.yaml
+project_path: /lite/_project.yaml
+book_path: /lite/_book.yaml
 description: <!--no description-->
 landing_page:
+  custom_css_path: /site-assets/css/style.css
   rows:
-  - heading: TensorFlow Lite is a lightweight solution for mobile and embedded devices.
+  - heading: TensorFlow Lite is for mobile and embedded devices.
+    description: >
+      <p style="max-width: 75%;">
+        TensorFlow Lite is the official solution for running machine learning
+        models on mobile and embedded devices. It enables on&#8209;device machine
+        learning inference with low latency and a small binary size on Android,
+        iOS, and other operating systems.
+      </p>
+      <style>
+      .tfo-landing-row-heading {
+        padding-top: 0 !important;
+      }
+      .tfo-landing-row-heading h2 {
+        margin-top: 0 !important;
+      }
+      .tfo-landing-row-heading-list ol, .tfo-landing-row-heading-list ul {
+        margin-top: 0;
+      }
+      </style>
+
+  - classname: tfo-landing-row-heading tfo-landing-row-heading-list
+    heading: Many benefits
+    description: >
+      On-device ML inference is difficult because of the many constraints—TensorFlow Lite can solve these:
     items:
-    - classname: devsite-landing-row-50
-      description: >
-        TensorFlow Lite is TensorFlow’s lightweight solution for mobile and
-        embedded devices. It enables on-device machine learning inference with
-        low latency and a small binary size. TensorFlow Lite also supports
-        hardware acceleration with the
-        <a href='https://developer.android.com/ndk/guides/neuralnetworks/index.html'>Android Neural Networks API</a>.
-      list:
-      - heading: Key point 1
+    - list:
+      - heading: Performance
+        description: >
+          TF Lite is fast with no noticeable accuracy loss—see the <a href="./performance">metrics</a>.
+        icon:
+          icon_name: lens
+          foreground: theme
+      - heading: Portability
         description: >
-          [high-level overview]
+          <a href="https://developer.android.com/ndk/guides/neuralnetworks/" class="external">Android</a>,
+          iOS, and more specialized IoT devices.
         icon:
-          icon_name: chevron_right
+          icon_name: lens
           foreground: theme
-          background: grey
-      - heading: Key point 2
+    - list:
+      - heading: Low latency
         description: >
-          [high-level overview]
+          Optimized float- and fixed-point CPU kernels, op&#8209;fusing, and more.
         icon:
-          icon_name: chevron_right
+          icon_name: lens
           foreground: theme
-          background: grey
-      - heading: Key point 3
+      - heading: Acceleration
         description: >
-          [high-level overview]
+          Integration with GPU and internal/external accelerators.
         icon:
-          icon_name: chevron_right
+          icon_name: lens
           foreground: theme
-          background: grey
-      code_block: |
-        <pre class = "prettyprint">
-        $ toco --input_file=$(pwd)/mobilenet_v1_1.0_224/frozen_graph.pb \
-               --input_format=TENSORFLOW_GRAPHDEF \
-               --output_format=TFLITE \
-               --output_file=/tmp/mobilenet_v1_1.0_224.tflite \
-               --inference_type=FLOAT \
-               --input_type=FLOAT \
-               --input_arrays=input \
-               --output_arrays=MobilenetV1/Predictions/Reshape_1 \
-               --input_shapes=1,224,224,3
-        </pre>
+    - list:
+      - heading: Small model size
+        description: >
+          Controlled dependencies, <a href="https://medium.com/tensorflow/introducing-the-model-optimization-toolkit-for-tensorflow-254aca1ba0a3" class="external">quantization</a>,
+          and op&nbsp;registration.
+        icon:
+          icon_name: lens
+          foreground: theme
+      - heading: Tooling
+        description: >
+          Conversion, compression, benchmarking, power-consumption, and more.
+        icon:
+          icon_name: lens
+          foreground: theme
+
+  - classname: devsite-landing-row-logos tfo-landing-row-heading
+    heading: Companies using TensorFlow Lite
+    items:
+    - custom_image:
+        path: ./images/landing-page/photos_logo.png
+      path: https://www.photos.google.com
+    - custom_image:
+        path: ./images/landing-page/gboard_logo.png
+      path: https://play.google.com/store/apps/details?id=com.google.android.inputmethod.latin&hl=en_US
+    - custom_image:
+        path: ./images/landing-page/gmail_logo.png
+      path: https://www.google.com/gmail/
+    - custom_image:
+        path: ./images/landing-page/assistant_logo.png
+      path: https://assistant.google.com/
+
+  - classname: devsite-landing-row-logos
+    items:
+    - custom_image:
+        path: ./images/landing-page/vsco_logo.png
+      path: https://vsco.co
+    - custom_image:
+        path: ./images/landing-page/shazam_logo.png
+      path: https://www.shazam.com/
+    - custom_image:
+        path: ./images/landing-page/nest_logo.png
+      path: https://nest.com/    
+    - custom_image:
+        path: ./images/landing-page/loseit_logo.png
+      path: https://www.loseit.com/
+
+  - classname: devsite-landing-row-no-image-background devsite-landing-row-67
+    background: grey
+    items:
+    - description: >
+        <em>“TensorFlow Lite helped us introduce machine learning and AI into our
+        app in an easy and streamlined way. We could reduce the size of our
+        models while keeping the accuracy high. This helped us create an amazing
+        fishing experience for our users by allowing them to identify any fish
+        species with just a photo.”</em>
+      image_path: ./images/landing-page/fishbrain_logo_big.png
+
+  - heading: How it works
+    items:
+    - heading: Build
+      icon:
+        icon_name: build
+      description: >
+        Build a new model or retrain an existing one, such as using transfer learning.
+      buttons:
+      - label: Read the developer guide
+        path: /lite/devguide
+        classname: button button-primary tfo-button-primary
+    - heading: Convert
+      icon:
+        icon_name: autorenew
+      description: >
+        Convert a TensorFlow model into a compressed flat buffer with the
+        TensorFlow Lite Optimizing Converter (TOCO).
+      buttons:
+      - label: Read the TOCO guide
+        path: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/lite/toco/g3doc/python_api.md
+        classname: button button-primary tfo-button-primary
+    - heading: Deploy
+      icon:
+        icon_name: bolt
+      description: >
+        Take the compressed <code>.tflite</code> file and load it into a mobile
+        or embedded device.<br/>
+        See the <a href="#build-your-first-tensorflow-lite-app">tutorials below</a> to build an app.
+
+  - heading: Build your first TensorFlow Lite app
+    background: grey
+    items:
+    - classname: tfo-landing-row-item-inset-white
+      heading: Get started
+      description: >
+        <ul>
+          <li>Beginner: <a href="https://codelabs.developers.google.com/codelabs/tensorflow-for-poets/" class="external">TensorFlow for Poets</a></li>
+          <li>Beginner: <a href="https://codelabs.developers.google.com/codelabs/tensorflow-for-poets-2-tflite/" class="external">TensorFlow for Poets 2: Android</a></li>
+          <li>Beginner: <a href="https://codelabs.developers.google.com/codelabs/tensorflow-for-poets-2-ios/" class="external">TensorFlow for Poets 2: iOS </a></li>
+          <li>Intermediate: <a href="https://medium.com/tensorflow/training-and-serving-a-realtime-mobile-object-detector-in-30-minutes-with-cloud-tpus-b78971cf1193" class="external">Object detection tutorial</a>
+        </ul>
+    - classname: tfo-landing-row-item-inset-white
+      heading: Share your TensorFlow Lite story
+      description: >
+        We love to hear what you're working on—it may even get highlighted on
+        our social media! <a href="https://groups.google.com/a/tensorflow.org/forum/#!forum/discuss" class="external">Tell us</a>.
+
+  - classname: devsite-landing-row-no-image-background devsite-landing-row-67
+    items:
+    - description: >
+        <p>
+          <em>“The release of TensorFlow Lite has allowed us to deploy an engaging
+          real-time experience to our users that eliminates the requirement
+          for a data connection. TensorFlow Lite’s ability to compress and
+          optimize the TensorFlow graph for mobile deployment has been
+          transformative in expanding the capabilities of Snap It.</em>
+        </p>
+        <p>
+          <em>Through TensorFlow Lite, our users can now enjoy a state of the
+          art, computer-vision-based food logging experience without worrying
+          about signal strength. We look forward to future collaborations
+          with the TensorFlow Lite team.”</em>
+        </p>
+      image_path: ./images/landing-page/loseit_logo_big.png
 
   - classname: devsite-landing-row-cards
+    background: grey
+    heading: Updates
     items:
+    - heading: Introducing the Model Optimization Toolkit
+      image_path: /ecosystem/images/tf-logo-card-16x9.png
+      path: https://medium.com/tensorflow/introducing-the-model-optimization-toolkit-for-tensorflow-254aca1ba0a3
+      buttons:
+      - label: Read on TensorFlow blog
+        path: https://medium.com/tensorflow/introducing-the-model-optimization-toolkit-for-tensorflow-254aca1ba0a3
+    - heading: East Africa Cassava App
+      image_path: ./images/landing-page/detect_crop_disease_in_africa.png
+      path: https://heartbeat.fritz.ai/community-spotlight-nuru-a-mobile-app-by-plantvillage-to-detect-crop-disease-in-africa-28d142bf63d5
+      buttons:
+      - label: Read more
+        path: https://heartbeat.fritz.ai/community-spotlight-nuru-a-mobile-app-by-plantvillage-to-detect-crop-disease-in-africa-28d142bf63d5
     - heading: Using TensorFlow Lite on Android
       image_path: /ecosystem/images/tf-logo-card-16x9.png
       path: https://medium.com/tensorflow/using-tensorflow-lite-on-android-9bbc9cb7d69d
       buttons:
       - label: Read on TensorFlow blog
         path: https://medium.com/tensorflow/using-tensorflow-lite-on-android-9bbc9cb7d69d
+
+  - classname: devsite-landing-row-cards
+    background: grey
+    items:
     - heading: TensorFlow Lite at the Dev Summit
       youtube_id: FAMfy7izB6A
       buttons:
@@ -66,3 +215,4 @@ landing_page:
       buttons:
       - label: View on GitHub
         path: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite
+    - classname: devsite-landing-row-item-hidden
diff --git a/tensorflow/contrib/lite/g3doc/_project.yaml b/tensorflow/contrib/lite/g3doc/_project.yaml
index b39666516b..d48d07be04 100644
--- a/tensorflow/contrib/lite/g3doc/_project.yaml
+++ b/tensorflow/contrib/lite/g3doc/_project.yaml
@@ -1,6 +1,6 @@
 name: TensorFlow Lite
-breadcrumb_name: Mobile
-home_url: /mobile/
+breadcrumb_name: TensorFlow Lite
+home_url: /lite/
 parent_project_metadata_path: /_project.yaml
 description: >
   TensorFlow Lite is a lightweight solution for mobile and embedded devices.
diff --git a/tensorflow/contrib/lite/g3doc/api_docs/python/_toc.yaml b/tensorflow/contrib/lite/g3doc/api_docs/python/_toc.yaml
deleted file mode 100644
index 1e1c44c692..0000000000
--- a/tensorflow/contrib/lite/g3doc/api_docs/python/_toc.yaml
+++ /dev/null
@@ -1,6 +0,0 @@
-# Automatically generated file; please do not edit
-toc:
-  - title: TensorFlow Lite
-    section:
-    - title: Overview
-      path: /mobile/api_docs/python/
diff --git a/tensorflow/contrib/lite/g3doc/devguide.md b/tensorflow/contrib/lite/g3doc/devguide.md
index 90e7915c52..0eed516000 100644
--- a/tensorflow/contrib/lite/g3doc/devguide.md
+++ b/tensorflow/contrib/lite/g3doc/devguide.md
@@ -1,5 +1,4 @@
-
-# Developer Guide
+# TF Lite Developer Guide
 
 Using a TensorFlow Lite model in your mobile app requires multiple
 considerations: you must choose a pre-trained or custom model, convert the model
@@ -55,7 +54,7 @@ both floating point and quantized inference.
 ### Train a custom model
 
 A developer may choose to train a custom model using Tensorflow (see the
-[TensorFlow tutorials](../../tutorials/) for examples of building and training
+[TensorFlow tutorials](../tutorials/) for examples of building and training
 models). If you have already written a model, the first step is to export this
 to a `tf.GraphDef` file. This is required because some formats do not store the
 model structure outside the code, and we must communicate with other parts of the
@@ -205,7 +204,7 @@ The open source Android demo app uses the JNI interface and is available
 [on GitHub](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/java/demo/app).
 You can also download a
 [prebuilt APK](http://download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk).
-See the <a href="../demo_android.md">Android demo</a> guide for details.
+See the <a href="./demo_android.md">Android demo</a> guide for details.
 
 The <a href="./android_build.md">Android mobile</a> guide has instructions for
 installing TensorFlow on Android and setting up `bazel` and Android Studio.
@@ -214,7 +213,7 @@ installing TensorFlow on Android and setting up `bazel` and Android Studio.
 
 To integrate a TensorFlow model in an iOS app, see the
 [TensorFlow Lite for iOS](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/g3doc/ios.md)
-guide and <a href="../demo_ios.md">iOS demo</a> guide.
+guide and <a href="./demo_ios.md">iOS demo</a> guide.
 
 #### Core ML support
 
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/assistant_logo.png b/tensorflow/contrib/lite/g3doc/images/landing-page/assistant_logo.png
new file mode 100644
index 0000000000..ced0872ab2
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/assistant_logo.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/detect_crop_disease_in_africa.png b/tensorflow/contrib/lite/g3doc/images/landing-page/detect_crop_disease_in_africa.png
new file mode 100644
index 0000000000..45b3b4f6fe
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/detect_crop_disease_in_africa.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/fishbrain_logo.png b/tensorflow/contrib/lite/g3doc/images/landing-page/fishbrain_logo.png
new file mode 100644
index 0000000000..bc1bf6e1e7
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/fishbrain_logo.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/fishbrain_logo_big.png b/tensorflow/contrib/lite/g3doc/images/landing-page/fishbrain_logo_big.png
new file mode 100644
index 0000000000..d76fca86a9
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/fishbrain_logo_big.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/gboard_logo.png b/tensorflow/contrib/lite/g3doc/images/landing-page/gboard_logo.png
new file mode 100644
index 0000000000..f1a93ab763
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/gboard_logo.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/gmail_logo.png b/tensorflow/contrib/lite/g3doc/images/landing-page/gmail_logo.png
new file mode 100644
index 0000000000..21aa2c84ea
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/gmail_logo.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/loseit_logo.png b/tensorflow/contrib/lite/g3doc/images/landing-page/loseit_logo.png
new file mode 100644
index 0000000000..b6b3d14df9
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/loseit_logo.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/loseit_logo_big.png b/tensorflow/contrib/lite/g3doc/images/landing-page/loseit_logo_big.png
new file mode 100644
index 0000000000..b3e46d4bd8
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/loseit_logo_big.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/nest_logo.png b/tensorflow/contrib/lite/g3doc/images/landing-page/nest_logo.png
new file mode 100644
index 0000000000..35bfd97373
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/nest_logo.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/photos_logo.png b/tensorflow/contrib/lite/g3doc/images/landing-page/photos_logo.png
new file mode 100644
index 0000000000..4333426dfe
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/photos_logo.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/shazam_logo.png b/tensorflow/contrib/lite/g3doc/images/landing-page/shazam_logo.png
new file mode 100644
index 0000000000..6ec412c75c
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/shazam_logo.png
diff --git a/tensorflow/contrib/lite/g3doc/images/landing-page/vsco_logo.png b/tensorflow/contrib/lite/g3doc/images/landing-page/vsco_logo.png
new file mode 100644
index 0000000000..f408f9024b
--- /dev/null
+++ b/tensorflow/contrib/lite/g3doc/images/landing-page/vsco_logo.png
diff --git a/tensorflow/contrib/lite/g3doc/tfmobile/index.md b/tensorflow/contrib/lite/g3doc/tfmobile/index.md
index d003bb2f38..49ad35d4e6 100644
--- a/tensorflow/contrib/lite/g3doc/tfmobile/index.md
+++ b/tensorflow/contrib/lite/g3doc/tfmobile/index.md
@@ -4,7 +4,7 @@
 TensorFlow was designed to be a good deep learning solution for mobile
 platforms. Currently we have two solutions for deploying machine learning
 applications on mobile and embedded devices: TensorFlow for Mobile and
-<a href="../index.md">TensorFlow Lite</a>.
+<a href="../../lite">TensorFlow Lite</a>.
 
 ## TensorFlow Lite versus TensorFlow Mobile