Merge changes from github.

END_PUBLIC

---
Commit b30ce4714 authored by James Qin<jamesqin@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Revamp CudnnRNN Saveables

1. Use a lossy way to save/restore cudnn biases during checkpointing.
Cudnn uses 2 biases each gate for all RNNs while tf uses one. To allow cudnn checkpoints
to be compatible with both Cudnn and platform-independent impls, previously both
individual bias and summed biases each gate were stored.
The new way only stores the bias sum for each gate, and split it half-half when
restoring from a cudnn graph. Doing this does not cause problems since RNNs do not use
weight-decay to regularize.

2. Use inheritance instead of branching
* Split RNNParamsSaveable to 1 base class and 4 subclasses.
* Extract common routines and only overwrite rnn-type-specific pieces in subclasses.

PiperOrigin-RevId: 166413989

---
Commit ebc421daf authored by Alan Yee<alyee@ucsd.edu>
Committed by Jonathan Hseu<vomjom@vomjom.net>:
Update documentation for contrib (#12424)

* Update __init__.py

Remove ## for standardization of api docs

* Create README.md

Add README to define this directory's purpose

* Update __init.py

Markdown styling does not show up well in api docs

* Update README.md

Add short mention of describing what to deprecate

* Update README.md

Capitalize title

* Update README.md

Revert README change

* Delete README.md

---
Commit fd295394d authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Use latest version of nsync library, which now allows use of cmake on MacOS.

PiperOrigin-RevId: 166411437

---
Commit 587d728e0 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[XLA] Refactor reduce-precision-insertion filters, add several more options.

In particular, this adds the ability to add reduce-precision operations after fusion nodes based on the contents of those fusion nodes, and the ability to filter operations based on the "op_name" metadata.

PiperOrigin-RevId: 166408392

---
Commit 3142f8ef5 authored by Ali Yahya<alive@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Steps toward making ResourceVariables compatible with Eager.

This change forces the value of the reuse flag in variable scopes to be tf.AUTO_REUSE when in Eager mode.

This change also adds comprehensive Eager tests for ResourceVariable.

PiperOrigin-RevId: 166408161

---
Commit b2ce45150 authored by Igor Ganichev<iga@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Make Graph::IsValidNode public

It can be reimplemented with existing public APIs, but instead of doing so,
making this one public seems better.

PiperOrigin-RevId: 166407897

---
Commit 0a2f40e92 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[XLA::CPU] Fix HLO profiling in parallel CPU backend.

PiperOrigin-RevId: 166400211

---
Commit c4a58e3fd authored by Yao Zhang<yaozhang@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Identify frame ids for all nodes in a graph.

PiperOrigin-RevId: 166397615

---
Commit 989713f26 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
BEGIN_PUBLIC
Automated g4 rollback of changelist 166294015

PiperOrigin-RevId: 166521502

2 files changed, 47 insertions, 18 deletions

diff --git a/tensorflow/contrib/android/cmake/CMakeLists.txt b/tensorflow/contrib/android/cmake/CMakeLists.txt
index 1f86288cf9..f61e9560ef 100644
--- a/tensorflow/contrib/android/cmake/CMakeLists.txt
+++ b/tensorflow/contrib/android/cmake/CMakeLists.txt
@@ -28,7 +28,7 @@ set_target_properties(lib_proto PROPERTIES IMPORTED_LOCATION
 
 add_library(lib_nsync STATIC IMPORTED )
 set_target_properties(lib_nsync PROPERTIES IMPORTED_LOCATION
-    ${TARGET_NSYNC_LIB})
+    ${TARGET_NSYNC_LIB}/lib/libnsync.a)
 
 add_library(lib_tf STATIC IMPORTED )
 set_target_properties(lib_tf PROPERTIES IMPORTED_LOCATION
diff --git a/tensorflow/contrib/android/java/org/tensorflow/contrib/android/TensorFlowInferenceInterface.java b/tensorflow/contrib/android/java/org/tensorflow/contrib/android/TensorFlowInferenceInterface.java
index 587f2941e5..9b7f394258 100644
--- a/tensorflow/contrib/android/java/org/tensorflow/contrib/android/TensorFlowInferenceInterface.java
+++ b/tensorflow/contrib/android/java/org/tensorflow/contrib/android/TensorFlowInferenceInterface.java
@@ -55,23 +55,7 @@ public class TensorFlowInferenceInterface {
    * @param model The filepath to the GraphDef proto representing the model.
    */
   public TensorFlowInferenceInterface(AssetManager assetManager, String model) {
-    Log.i(TAG, "Checking to see if TensorFlow native methods are already loaded");
-    try {
-      // Hack to see if the native libraries have been loaded.
-      new RunStats();
-      Log.i(TAG, "TensorFlow native methods already loaded");
-    } catch (UnsatisfiedLinkError e1) {
-      Log.i(
-          TAG, "TensorFlow native methods not found, attempting to load via tensorflow_inference");
-      try {
-        System.loadLibrary("tensorflow_inference");
-        Log.i(TAG, "Successfully loaded TensorFlow native methods (RunStats error may be ignored)");
-      } catch (UnsatisfiedLinkError e2) {
-        throw new RuntimeException(
-            "Native TF methods not found; check that the correct native"
-                + " libraries are present in the APK.");
-      }
-    }
+    prepareNativeRuntime();
 
     this.modelName = model;
     this.g = new Graph();
@@ -102,6 +86,31 @@ public class TensorFlowInferenceInterface {
       throw new RuntimeException("Failed to load model from '" + model + "'", e);
     }
   }
+    
+  /*
+   * Load a TensorFlow model from provided InputStream.
+   * Note: The InputStream will not be closed after loading model, users need to
+   * close it themselves.
+   *
+   * @param is The InputStream to use to load the model.
+   */
+  public TensorFlowInferenceInterface(InputStream is) {
+    prepareNativeRuntime();
+    
+    // modelName is redundant for model loading from input stream, here is for
+    // avoiding error in initialization as modelName is marked final.
+    this.modelName = "";
+    this.g = new Graph();
+    this.sess = new Session(g);
+    this.runner = sess.runner();
+
+    try {
+      loadGraph(is, g);
+      Log.i(TAG, "Successfully loaded model from the input stream");
+    } catch (IOException e) {
+      throw new RuntimeException("Failed to load model from the input stream", e);
+    }
+  }
 
   /**
    * Runs inference between the previously registered input nodes (via feed*) and the requested
@@ -408,6 +417,26 @@ public class TensorFlowInferenceInterface {
   public void fetch(String outputName, ByteBuffer dst) {
     getTensor(outputName).writeTo(dst);
   }
+  
+  private void prepareNativeRuntime() {
+    Log.i(TAG, "Checking to see if TensorFlow native methods are already loaded");
+    try {
+      // Hack to see if the native libraries have been loaded.
+      new RunStats();
+      Log.i(TAG, "TensorFlow native methods already loaded");
+    } catch (UnsatisfiedLinkError e1) {
+      Log.i(
+          TAG, "TensorFlow native methods not found, attempting to load via tensorflow_inference");
+      try {
+        System.loadLibrary("tensorflow_inference");
+        Log.i(TAG, "Successfully loaded TensorFlow native methods (RunStats error may be ignored)");
+      } catch (UnsatisfiedLinkError e2) {
+        throw new RuntimeException(
+            "Native TF methods not found; check that the correct native"
+                + " libraries are present in the APK.");
+      }
+    }
+  }
 
   private void loadGraph(InputStream is, Graph g) throws IOException {
     final long startMs = System.currentTimeMillis();