Merge changes from github.

PiperOrigin-RevId: 189945839

6 files changed, 85 insertions, 10 deletions

diff --git a/tensorflow/examples/android/AndroidManifest.xml b/tensorflow/examples/android/AndroidManifest.xml
index bb75431a1f..5c47ce6b67 100644
--- a/tensorflow/examples/android/AndroidManifest.xml
+++ b/tensorflow/examples/android/AndroidManifest.xml
@@ -40,6 +40,7 @@
             <intent-filter>
                 <action android:name="android.intent.action.MAIN" />
                 <category android:name="android.intent.category.LAUNCHER" />
+                <category android:name="android.intent.category.LEANBACK_LAUNCHER" />
             </intent-filter>
         </activity>
 
@@ -49,6 +50,7 @@
             <intent-filter>
                 <action android:name="android.intent.action.MAIN" />
                 <category android:name="android.intent.category.LAUNCHER" />
+                <category android:name="android.intent.category.LEANBACK_LAUNCHER" />
             </intent-filter>
         </activity>
 
@@ -58,6 +60,7 @@
             <intent-filter>
                 <action android:name="android.intent.action.MAIN" />
                 <category android:name="android.intent.category.LAUNCHER" />
+                <category android:name="android.intent.category.LEANBACK_LAUNCHER" />
             </intent-filter>
         </activity>
 
@@ -67,6 +70,7 @@
             <intent-filter>
                 <action android:name="android.intent.action.MAIN" />
                 <category android:name="android.intent.category.LAUNCHER" />
+                <category android:name="android.intent.category.LEANBACK_LAUNCHER" />
             </intent-filter>
         </activity>
     </application>
diff --git a/tensorflow/examples/android/src/org/tensorflow/demo/CameraActivity.java b/tensorflow/examples/android/src/org/tensorflow/demo/CameraActivity.java
index 8bd4abb154..429138abe5 100644
--- a/tensorflow/examples/android/src/org/tensorflow/demo/CameraActivity.java
+++ b/tensorflow/examples/android/src/org/tensorflow/demo/CameraActivity.java
@@ -351,6 +351,10 @@ public abstract class CameraActivity extends Activity
 
   protected void setFragment() {
     String cameraId = chooseCamera();
+    if (cameraId == null) {
+      Toast.makeText(this, "No Camera Detected", Toast.LENGTH_SHORT).show();
+      finish();
+    }
 
     Fragment fragment;
     if (useCamera2API) {
@@ -416,7 +420,8 @@ public abstract class CameraActivity extends Activity
 
   @Override
   public boolean onKeyDown(final int keyCode, final KeyEvent event) {
-    if (keyCode == KeyEvent.KEYCODE_VOLUME_DOWN || keyCode == KeyEvent.KEYCODE_VOLUME_UP) {
+    if (keyCode == KeyEvent.KEYCODE_VOLUME_DOWN || keyCode == KeyEvent.KEYCODE_VOLUME_UP
+            || keyCode == KeyEvent.KEYCODE_BUTTON_L1 || keyCode == KeyEvent.KEYCODE_DPAD_CENTER) {
       debug = !debug;
       requestRender();
       onSetDebug(debug);
diff --git a/tensorflow/examples/android/src/org/tensorflow/demo/StylizeActivity.java b/tensorflow/examples/android/src/org/tensorflow/demo/StylizeActivity.java
index 6a66ec3927..33ec65e9f7 100644
--- a/tensorflow/examples/android/src/org/tensorflow/demo/StylizeActivity.java
+++ b/tensorflow/examples/android/src/org/tensorflow/demo/StylizeActivity.java
@@ -16,8 +16,10 @@
 
 package org.tensorflow.demo;
 
+import android.app.UiModeManager;
 import android.content.Context;
 import android.content.res.AssetManager;
+import android.content.res.Configuration;
 import android.graphics.Bitmap;
 import android.graphics.Bitmap.Config;
 import android.graphics.BitmapFactory;
@@ -31,9 +33,11 @@ import android.graphics.Typeface;
 import android.media.ImageReader.OnImageAvailableListener;
 import android.os.Bundle;
 import android.os.SystemClock;
+import android.util.DisplayMetrics;
 import android.util.Size;
 import android.util.TypedValue;
 import android.view.Display;
+import android.view.KeyEvent;
 import android.view.MotionEvent;
 import android.view.View;
 import android.view.View.OnClickListener;
@@ -43,6 +47,7 @@ import android.widget.BaseAdapter;
 import android.widget.Button;
 import android.widget.GridView;
 import android.widget.ImageView;
+import android.widget.RelativeLayout;
 import android.widget.Toast;
 import java.io.IOException;
 import java.io.InputStream;
@@ -381,6 +386,27 @@ public class StylizeActivity extends CameraActivity implements OnImageAvailableL
     grid = (GridView) findViewById(R.id.grid_layout);
     grid.setAdapter(adapter);
     grid.setOnTouchListener(gridTouchAdapter);
+
+    // Change UI on Android TV
+    UiModeManager uiModeManager = (UiModeManager) getSystemService(UI_MODE_SERVICE);
+    if (uiModeManager.getCurrentModeType() == Configuration.UI_MODE_TYPE_TELEVISION) {
+      DisplayMetrics displayMetrics = new DisplayMetrics();
+      getWindowManager().getDefaultDisplay().getMetrics(displayMetrics);
+      int styleSelectorHeight = displayMetrics.heightPixels;
+      int styleSelectorWidth = displayMetrics.widthPixels - styleSelectorHeight;
+      RelativeLayout.LayoutParams layoutParams = new RelativeLayout.LayoutParams(styleSelectorWidth, ViewGroup.LayoutParams.MATCH_PARENT);
+
+      // Calculate number of style in a row, so all the style can show up without scrolling
+      int numOfStylePerRow = 3;
+      while (styleSelectorWidth / numOfStylePerRow * Math.ceil((float) (adapter.getCount() - 2) / numOfStylePerRow) > styleSelectorHeight) {
+        numOfStylePerRow++;
+      }
+      grid.setNumColumns(numOfStylePerRow);
+      layoutParams.addRule(RelativeLayout.ALIGN_PARENT_RIGHT);
+      grid.setLayoutParams(layoutParams);
+      adapter.buttons.clear();
+    }
+
     setStyle(adapter.items[0], 1.0f);
   }
 
@@ -602,4 +628,38 @@ public class StylizeActivity extends CameraActivity implements OnImageAvailableL
 
     borderedText.drawLines(canvas, 10, canvas.getHeight() - 10, lines);
   }
+
+  @Override
+  public boolean onKeyDown(int keyCode, KeyEvent event) {
+    int moveOffset = 0;
+    switch (keyCode) {
+      case KeyEvent.KEYCODE_DPAD_LEFT:
+        moveOffset = -1;
+        break;
+      case KeyEvent.KEYCODE_DPAD_RIGHT:
+        moveOffset = 1;
+        break;
+      case KeyEvent.KEYCODE_DPAD_UP:
+        moveOffset = -1 * grid.getNumColumns();
+        break;
+      case KeyEvent.KEYCODE_DPAD_DOWN:
+        moveOffset = grid.getNumColumns();
+        break;
+      default:
+        return super.onKeyDown(keyCode, event);
+    }
+
+    // get the highest selected style
+    int currentSelect = 0;
+    float highestValue = 0;
+    for (int i = 0; i < adapter.getCount(); i++) {
+      if (adapter.items[i].value > highestValue) {
+        currentSelect = i;
+        highestValue = adapter.items[i].value;
+      }
+    }
+    setStyle(adapter.items[(currentSelect + moveOffset + adapter.getCount()) % adapter.getCount()], 1);
+
+    return true;
+  }
 }
diff --git a/tensorflow/examples/ios/README.md b/tensorflow/examples/ios/README.md
index 5bdaeb43ce..5d7bd36837 100644
--- a/tensorflow/examples/ios/README.md
+++ b/tensorflow/examples/ios/README.md
@@ -119,11 +119,13 @@ rundown:
    `tensorflow/contrib/makefile/gen/lib` to the Library Search Paths setting.
 
  - You'll also need to add `libprotobuf.a` and `libprotobuf-lite.a` from
-   `tensorflow/contrib/makefile/gen/protobuf_ios/lib` to your _Build Stages_ and
-   _Library Search Paths_.
+   `tensorflow/contrib/makefile/gen/protobuf_ios/lib`
+   and `nsync.a` from `tensorflow/contrib/makefile/downloads/nsync/builds/lipo.ios.c++11` 
+   to your _Build Stages_ and _Library Search Paths_.
 
  - The _Header Search_ paths needs to contain:
    - the root folder of tensorflow,
+   - `tensorflow/contrib/makefile/downloads/nsync/public`
    - `tensorflow/contrib/makefile/downloads/protobuf/src`
    - `tensorflow/contrib/makefile/downloads`,
    - `tensorflow/contrib/makefile/downloads/eigen`, and
diff --git a/tensorflow/examples/learn/mnist.py b/tensorflow/examples/learn/mnist.py
index 98819b20bf..3ead8614b6 100644
--- a/tensorflow/examples/learn/mnist.py
+++ b/tensorflow/examples/learn/mnist.py
@@ -61,8 +61,10 @@ def conv_model(features, labels, mode):
 
   # Densely connected layer with 1024 neurons.
   h_fc1 = tf.layers.dense(h_pool2_flat, 1024, activation=tf.nn.relu)
-  if mode == tf.estimator.ModeKeys.TRAIN:
-    h_fc1 = tf.layers.dropout(h_fc1, rate=0.5)
+  h_fc1 = tf.layers.dropout(
+      h_fc1, 
+      rate=0.5, 
+      training=(mode == tf.estimator.ModeKeys.TRAIN))
 
   # Compute logits (1 per class) and compute loss.
   logits = tf.layers.dense(h_fc1, N_DIGITS, activation=None)
diff --git a/tensorflow/examples/learn/resnet.py b/tensorflow/examples/learn/resnet.py
index 9542e55250..c00de932a8 100755
--- a/tensorflow/examples/learn/resnet.py
+++ b/tensorflow/examples/learn/resnet.py
@@ -53,6 +53,8 @@ def res_net_model(features, labels, mode):
     ndim = int(sqrt(input_shape[1]))
     x = tf.reshape(x, [-1, ndim, ndim, 1])
 
+  training = (mode == tf.estimator.ModeKeys.TRAIN)
+  
   # First convolution expands to 64 channels
   with tf.variable_scope('conv_layer1'):
     net = tf.layers.conv2d(
@@ -60,7 +62,7 @@ def res_net_model(features, labels, mode):
         filters=64,
         kernel_size=7,
         activation=tf.nn.relu)
-    net = tf.layers.batch_normalization(net)
+    net = tf.layers.batch_normalization(net, training=training)
 
   # Max pool
   net = tf.layers.max_pooling2d(
@@ -88,7 +90,7 @@ def res_net_model(features, labels, mode):
             kernel_size=1,
             padding='valid',
             activation=tf.nn.relu)
-        conv = tf.layers.batch_normalization(conv)
+        conv = tf.layers.batch_normalization(conv, training=training)
 
       with tf.variable_scope(name + '/conv_bottleneck'):
         conv = tf.layers.conv2d(
@@ -97,7 +99,7 @@ def res_net_model(features, labels, mode):
             kernel_size=3,
             padding='same',
             activation=tf.nn.relu)
-        conv = tf.layers.batch_normalization(conv)
+        conv = tf.layers.batch_normalization(conv, training=training)
 
       # 1x1 convolution responsible for restoring dimension
       with tf.variable_scope(name + '/conv_out'):
@@ -108,7 +110,7 @@ def res_net_model(features, labels, mode):
             kernel_size=1,
             padding='valid',
             activation=tf.nn.relu)
-        conv = tf.layers.batch_normalization(conv)
+        conv = tf.layers.batch_normalization(conv, training=training)
 
       # shortcut connections that turn the network into its counterpart
       # residual function (identity shortcut)
@@ -154,7 +156,7 @@ def res_net_model(features, labels, mode):
   loss = tf.losses.sparse_softmax_cross_entropy(labels=labels, logits=logits)
 
   # Create training op.
-  if mode == tf.estimator.ModeKeys.TRAIN:
+  if training:
     optimizer = tf.train.AdagradOptimizer(learning_rate=0.01)
     train_op = optimizer.minimize(loss, global_step=tf.train.get_global_step())
     return tf.estimator.EstimatorSpec(mode, loss=loss, train_op=train_op)