Update iOS examples to use CocoaPods, and moved to tensorflow/examples/ios

PiperOrigin-RevId: 158289285
author: A. Unique TensorFlower <gardener@tensorflow.org> 2017-06-07 10:59:18 -0700
committer: TensorFlower Gardener <gardener@tensorflow.org> 2017-06-07 11:03:49 -0700
commit: fdb8e29354ce93afa8c2335a6287a59eb37d42fc (patch)
tree: 75489b1dc9b502d0cde992f3faf21fbc6ef39be5 /tensorflow/examples/ios
parent: dffea202a506d7d0f5c2fb32798aecdcb1bab32a (diff)
40 files changed, 3844 insertions, 0 deletions
diff --git a/tensorflow/examples/ios/.gitignore b/tensorflow/examples/ios/.gitignore
new file mode 100644
index 0000000000..e572b3012c
--- /dev/null
+++ b/tensorflow/examples/ios/.gitignore
@@ -0,0 +1,4 @@
+project.xcworkspace
+xcuserdata
+imagenet_comp_graph_label_strings.txt
+tensorflow_inception_graph.pb
diff --git a/tensorflow/examples/ios/README.md b/tensorflow/examples/ios/README.md
new file mode 100644
index 0000000000..9832399d72
--- /dev/null
+++ b/tensorflow/examples/ios/README.md
@@ -0,0 +1,194 @@
+# TensorFlow iOS Examples
+
+This folder contains examples of how to build applications for iOS devices using TensorFlow.
+
+## Running the Samples using CocoaPod
+ - You'll need Xcode 7.3 or later.
+
+ - There are currently three examples: simple, benchmark, and camera. For now,
+   you can download the sample code by cloning the main tensorflow repository 
+   (we are planning to make the samples available as a separate repository
+   later).
+
+ - From the root of the tensorflow folder, download
+   [Inception v1](https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip),
+   and extract the label and graph files into the data folders inside both the
+   simple and camera examples:
+
+```bash
+mkdir -p ~/graphs
+curl -o ~/graphs/inception5h.zip \
+ https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip \
+ && unzip ~/graphs/inception5h.zip -d ~/graphs/inception5h
+cp ~/graphs/inception5h/* tensorflow/contrib/ios_examples/benchmark/data/
+cp ~/graphs/inception5h/* tensorflow/contrib/ios_examples/camera/data/
+cp ~/graphs/inception5h/* tensorflow/contrib/ios_examples/simple/data/
+```
+
+ - Change directory to one of the samples, download the TensorFlow-experimental
+   pod, and open the Xcode workspace. Observe: installing the pod can take a
+   long time since it is big (~450MB). For example, if you want to run the
+   simple example, then:
+```bash
+cd tensorflow/contrib/ios_examples/simple
+pod install
+open tf_simple_example.xcworkspace # obs, not the .xcodeproj directory
+```
+
+ - Run the simple app in the simulator. You should see a single-screen app with
+   a "Run Model" button. Tap that, and you should see some debug output appear
+   below indicating that the example Grace Hopper image in directory data has
+   been analyzed, with a military uniform recognized.
+
+ - Run the other samples using the same process. The camera example requires a
+   real device connected. Once you build and run that, you should get a live
+   camera view that you can point at objects to get real-time recognition
+   results.
+
+### Troubleshooting
+
+ - Make sure you use the TensorFlow-experimental pod (and not TensorFlow).
+  
+ - The TensorFlow-experimental pod is current about ~450MB. The reason it is 
+   so big is because we are bundling multiple platforms, and the pod includes
+   all TensorFlow functionality (e.g. operations). This is convenient during
+   development, but see below section on how you can build your own custom
+   TensorFlow library to reduce the size.
+
+### Creating Your own App
+
+ - Create your own app using Xcode then add a file named Podfile at the project
+   root directory with the following content:
+```bash
+target 'YourProjectName'
+       pod 'TensorFlow-experimental'
+```
+
+ - Then you run ```pod install``` to download and install the
+ TensorFlow-experimental pod, and finaly perform
+ ```open YourProjectName.xcworkspace``` and add your code.
+
+ - In your apps "Build Settings", make sure to add $(inherited) to sections
+   "Other Linker Flags", and "Header Search Paths".
+
+ - That's it. If you want to create your custom TensorFlow iOS library, for
+   example to reduce binary footprint, see below section.
+
+## Building the TensorFlow iOS libraries from source
+
+ - You'll need Xcode 7.3 or later, with the command-line tools installed.
+
+ - Follow the instructions at
+   [tensorflow/contrib/makefile](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/makefile)
+   under "iOS" to compile a static library containing the core TensorFlow code.
+
+ - You should see a single-screen app with a "Run Model" button. Tap that, and
+   you should see some debug output appear below indicating that the example
+   Grace Hopper image has been analyzed, with a military uniform recognized.
+
+ - Once you have success there, make sure you have a real device connected and
+   open up the Xcode project in the `camera` subfolder. Once you build and run
+   that, you should get a live camera view that you can point at objects to get
+   real-time recognition results.
+   
+### Troubleshooting
+
+If you're hitting problems, here's a checklist of common things to investigate:
+
+ - Make sure that you've run the `build_all_ios.sh` script.
+   This will run `download_dependencies.sh`,`compile_ios_protobuf.sh` and `compile_ios_tensorflow.sh`.
+   (check each one if they have run successful.)
+
+ - Check that you have version 7.3 of Xcode.
+
+ - If there's a complaint about no Sessions registered, that means that the C++
+   global constructors that TensorFlow relies on for registration haven't been
+   linked in properly. You'll have to make sure your project uses force_load, as
+   described below.
+
+### Creating your Own App from your source libraries
+
+You'll need to update various settings in your app to link against
+TensorFlow. You can view them in the example projects, but here's a full
+rundown:
+
+ - The `compile_ios_tensorflow.sh` script builds a universal static library in
+   `tensorflow/contrib/makefile/gen/lib/libtensorflow-core.a`. You'll need to add
+   this to your linking build stage, and in Search Paths add
+   `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_.
+
+ - The _Header Search_ paths needs to contain:
+   - the root folder of tensorflow,
+   - `tensorflow/contrib/makefile/downloads/protobuf/src`
+   - `tensorflow/contrib/makefile/downloads`,
+   - `tensorflow/contrib/makefile/downloads/eigen`, and
+   - `tensorflow/contrib/makefile/gen/proto`.
+
+ - In the Linking section, you need to add `-force_load` followed by the path to
+   the TensorFlow static library in the _Other Linker_ Flags section. This ensures
+   that the global C++ objects that are used to register important classes
+   inside the library are not stripped out. To the linker, they can appear
+   unused because no other code references the variables, but in fact their
+   constructors have the important side effect of registering the class.
+
+ - You'll need to include the Accelerate framework in the "Link Binary with
+   Libraries" build phase of your project.
+
+ - C++11 support (or later) should be enabled by setting `C++ Language Dialect` to
+   `GNU++11` (or `GNU++14`), and `C++ Standard Library` to `libc++`.
+
+ - The library doesn't currently support bitcode, so you'll need to disable that
+   in your project settings.
+
+ - Remove any use of the `-all_load` flag in your project. The protocol buffers
+   libraries (full and lite versions) contain duplicate symbols, and the `-all_load`
+   flag will cause these duplicates to become link errors. If you were using
+   `-all_load` to avoid issues with Objective-C categories in static libraries,
+   you may be able to replace it with the `-ObjC` flag.
+
+### Reducing the binary size
+
+TensorFlow is a comparatively large library for a mobile device, so it will
+increase the size of your app. Currently on iOS we see around a 11 MB binary
+footprint per CPU architecture, though we're actively working on reducing that.
+It can be tricky to set up the right configuration in your own app to keep the
+size minimized, so if you do run into this issue we recommend you start by
+looking at the simple example to examine its size. Here's how you do that:
+
+ - Open the Xcode project in tensorflow/contrib/ios_examples/simple.
+
+ - Make sure you've followed the steps above to get the data files.
+
+ - Choose "Generic iOS Device" as the build configuration.
+
+ - Select Product->Build.
+
+ - Once the build's complete, open the Report Navigator and select the logs.
+
+ - Near the bottom, you'll see a line saying "Touch tf_simple_example.app".
+
+ - Expand that line using the icon on the right, and copy the first argument to
+   the Touch command.
+
+ - Go to the terminal, type `ls -lah ` and then paste the path you copied.
+
+ - For example it might look like `ls -lah /Users/petewarden/Library/Developer/Xcode/DerivedData/tf_simple_example-etdbksqytcnzeyfgdwiihzkqpxwr/Build/Products/Debug-iphoneos/tf_simple_example.app`
+
+ - Running this command will show the size of the executable as the
+   `tf_simple_example` line.
+
+Right now you'll see a size of around 23 MB, since it's including two
+architectures (armv7 and arm64). As a first step, you should make sure the size
+increase you see in your own app is similar, and if it's larger, look at the
+"Other Linker Flags" used in the Simple Xcode project settings to strip the
+executable.
+
+After that, you can manually look at modifying the list of kernels
+included in tensorflow/contrib/makefile/tf_op_files.txt to reduce the number of
+implementations to the ones you're actually using in your own model. We're
+hoping to automate this step in the future, but for now manually removing them
+is the best approach.
diff --git a/tensorflow/examples/ios/benchmark/AppDelegate.h b/tensorflow/examples/ios/benchmark/AppDelegate.h
new file mode 100644
index 0000000000..94046d9728
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/AppDelegate.h
@@ -0,0 +1,21 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <UIKit/UIKit.h>
+
+@interface AppDelegate : UIResponder<UIApplicationDelegate>
+
+@property(strong, nonatomic) UIWindow *window;
+
+@end
diff --git a/tensorflow/examples/ios/benchmark/AppDelegate.mm b/tensorflow/examples/ios/benchmark/AppDelegate.mm
new file mode 100644
index 0000000000..23ffba0f7b
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/AppDelegate.mm
@@ -0,0 +1,44 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import "AppDelegate.h"
+
+#import "BenchmarkViewController.h"
+
+@implementation AppDelegate
+
+- (BOOL)application:(UIApplication *)application
+    didFinishLaunchingWithOptions:(NSDictionary *)launchOptions {
+
+  UITabBarController *bar = [[UITabBarController alloc] init];
+  [bar setViewControllers:
+      @[[[BenchmarkViewController alloc] init]]];
+  bar.selectedIndex = 0;
+  self.window = [[UIWindow alloc] initWithFrame:[[UIScreen mainScreen] bounds]];
+  self.window.rootViewController = bar;
+  [self.window makeKeyAndVisible];
+  return YES;
+}
+
+- (void)applicationWillResignActive:(UIApplication *)application {}
+
+- (void)applicationDidEnterBackground:(UIApplication *)application {}
+
+- (void)applicationWillEnterForeground:(UIApplication *)application {}
+
+- (void)applicationDidBecomeActive:(UIApplication *)application {}
+
+- (void)applicationWillTerminate:(UIApplication *)application {}
+
+@end
diff --git a/tensorflow/examples/ios/benchmark/Benchmark-Info.plist b/tensorflow/examples/ios/benchmark/Benchmark-Info.plist
new file mode 100644
index 0000000000..0cdbf28a31
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/Benchmark-Info.plist
@@ -0,0 +1,47 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
+<plist version="1.0">
+<dict>
+	<key>CFBundleDevelopmentRegion</key>
+	<string>en</string>
+	<key>CFBundleDisplayName</key>
+	<string>tf_benchmark_example</string>
+	<key>CFBundleExecutable</key>
+	<string>tf_benchmark_example</string>
+	<key>CFBundleIdentifier</key>
+	<string>com.google.tf_benchmark_example</string>
+	<key>CFBundleInfoDictionaryVersion</key>
+	<string>6.0</string>
+	<key>CFBundleName</key>
+	<string>ios-app</string>
+	<key>CFBundlePackageType</key>
+	<string>APPL</string>
+	<key>CFBundleShortVersionString</key>
+	<string>1.0</string>
+	<key>CFBundleSignature</key>
+	<string>????</string>
+	<key>CFBundleVersion</key>
+	<string>1.0</string>
+	<key>LSRequiresIPhoneOS</key>
+	<true/>
+	<key>UILaunchStoryboardName</key>
+	<string>BenchmarkViewController</string>
+	<key>UIRequiredDeviceCapabilities</key>
+	<array>
+		<string>armv7</string>
+	</array>
+	<key>UISupportedInterfaceOrientations</key>
+	<array>
+		<string>UIInterfaceOrientationPortrait</string>
+		<string>UIInterfaceOrientationLandscapeLeft</string>
+		<string>UIInterfaceOrientationLandscapeRight</string>
+	</array>
+	<key>UISupportedInterfaceOrientations~ipad</key>
+	<array>
+		<string>UIInterfaceOrientationPortrait</string>
+		<string>UIInterfaceOrientationPortraitUpsideDown</string>
+		<string>UIInterfaceOrientationLandscapeLeft</string>
+		<string>UIInterfaceOrientationLandscapeRight</string>
+	</array>
+</dict>
+</plist>
diff --git a/tensorflow/examples/ios/benchmark/BenchmarkViewController.h b/tensorflow/examples/ios/benchmark/BenchmarkViewController.h
new file mode 100644
index 0000000000..c9cbc49280
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/BenchmarkViewController.h
@@ -0,0 +1,24 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <UIKit/UIKit.h>
+
+@interface BenchmarkViewController : UIViewController
+
+- (IBAction)getUrl:(id)sender;
+
+@property(weak, nonatomic) IBOutlet UITextView *urlContentTextView;
+@property(weak, nonatomic) IBOutlet UITextField *urlTextField;
+
+@end
diff --git a/tensorflow/examples/ios/benchmark/BenchmarkViewController.mm b/tensorflow/examples/ios/benchmark/BenchmarkViewController.mm
new file mode 100644
index 0000000000..cab7b36f17
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/BenchmarkViewController.mm
@@ -0,0 +1,302 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import "BenchmarkViewController.h"
+
+#include <pthread.h>
+#include <sys/time.h>
+#include <unistd.h>
+#include <fstream>
+#include <queue>
+#include <sstream>
+#include <string>
+
+//#include "google/protobuf/io/coded_stream.h"
+//#include "google/protobuf/io/zero_copy_stream_impl.h"
+//#include "google/protobuf/io/zero_copy_stream_impl_lite.h"
+//#include "google/protobuf/message_lite.h"
+#include "tensorflow/core/framework/op_kernel.h"
+//#include "tensorflow/core/framework/tensor.h"
+//#include "tensorflow/core/framework/types.pb.h"
+//#include "tensorflow/core/platform/env.h"
+//#include "tensorflow/core/platform/logging.h"
+//#include "tensorflow/core/platform/mutex.h"
+//#include "tensorflow/core/platform/types.h"
+#include "tensorflow/core/public/session.h"
+#include "tensorflow/core/util/stat_summarizer.h"
+
+#include "ios_image_load.h"
+
+NSString* RunInferenceOnImage();
+
+namespace {
+class IfstreamInputStream : public ::google::protobuf::io::CopyingInputStream {
+ public:
+  explicit IfstreamInputStream(const std::string& file_name)
+      : ifs_(file_name.c_str(), std::ios::in | std::ios::binary) {}
+  ~IfstreamInputStream() { ifs_.close(); }
+
+  int Read(void* buffer, int size) {
+    if (!ifs_) {
+      return -1;
+    }
+    ifs_.read(static_cast<char*>(buffer), size);
+    return (int)ifs_.gcount();
+  }
+
+ private:
+  std::ifstream ifs_;
+};
+}  // namespace
+
+@interface BenchmarkViewController ()
+@end
+
+@implementation BenchmarkViewController {
+}
+
+- (IBAction)getUrl:(id)sender {
+  NSString* inference_result = RunInferenceOnImage();
+  self.urlContentTextView.text = inference_result;
+}
+
+@end
+
+// Returns the top N confidence values over threshold in the provided vector,
+// sorted by confidence in descending order.
+static void GetTopN(
+    const Eigen::TensorMap<Eigen::Tensor<float, 1, Eigen::RowMajor>,
+                           Eigen::Aligned>& prediction,
+    const int num_results, const float threshold,
+    std::vector<std::pair<float, int>>* top_results) {
+  // Will contain top N results in ascending order.
+  std::priority_queue<std::pair<float, int>, std::vector<std::pair<float, int>>,
+                      std::greater<std::pair<float, int>>>
+      top_result_pq;
+
+  long count = prediction.size();
+  for (int i = 0; i < count; ++i) {
+    const float value = prediction(i);
+
+    // Only add it if it beats the threshold and has a chance at being in
+    // the top N.
+    if (value < threshold) {
+      continue;
+    }
+
+    top_result_pq.push(std::pair<float, int>(value, i));
+
+    // If at capacity, kick the smallest value out.
+    if (top_result_pq.size() > num_results) {
+      top_result_pq.pop();
+    }
+  }
+
+  // Copy to output vector and reverse into descending order.
+  while (!top_result_pq.empty()) {
+    top_results->push_back(top_result_pq.top());
+    top_result_pq.pop();
+  }
+  std::reverse(top_results->begin(), top_results->end());
+}
+
+bool PortableReadFileToProto(const std::string& file_name,
+                             ::google::protobuf::MessageLite* proto) {
+  ::google::protobuf::io::CopyingInputStreamAdaptor stream(
+      new IfstreamInputStream(file_name));
+  stream.SetOwnsCopyingStream(true);
+  // TODO(jiayq): the following coded stream is for debugging purposes to allow
+  // one to parse arbitrarily large messages for MessageLite. One most likely
+  // doesn't want to put protobufs larger than 64MB on Android, so we should
+  // eventually remove this and quit loud when a large protobuf is passed in.
+  ::google::protobuf::io::CodedInputStream coded_stream(&stream);
+  // Total bytes hard limit / warning limit are set to 1GB and 512MB
+  // respectively.
+  coded_stream.SetTotalBytesLimit(1024LL << 20, 512LL << 20);
+  return proto->ParseFromCodedStream(&coded_stream);
+}
+
+NSString* FilePathForResourceName(NSString* name, NSString* extension) {
+  NSString* file_path =
+      [[NSBundle mainBundle] pathForResource:name ofType:extension];
+  if (file_path == NULL) {
+    LOG(FATAL) << "Couldn't find '" << [name UTF8String] << "."
+               << [extension UTF8String] << "' in bundle.";
+  }
+  return file_path;
+}
+
+// A utility function to get the current time in seconds, for simple profiling.
+double time() {
+  timeval t;
+  gettimeofday(&t, nullptr);
+  return t.tv_sec + 1e-6 * t.tv_usec;
+}
+
+// Runs the session with profiling enabled, and prints out details of the time
+// that each node in the graph takes to the debug log.
+tensorflow::Status BenchmarkInference(
+    tensorflow::Session* session,
+    const std::vector<std::pair<tensorflow::string, tensorflow::Tensor>> inputs,
+    const std::vector<tensorflow::string>& output_layer_names,
+    std::vector<tensorflow::Tensor>* output_layers,
+    tensorflow::StatSummarizer* stat_summarizer, double* average_time) {
+  tensorflow::Status run_status;
+  const int iterations_count = 20;
+  double total_time = 0.0;
+  tensorflow::RunOptions run_options;
+  run_options.set_trace_level(tensorflow::RunOptions::FULL_TRACE);
+  tensorflow::RunMetadata run_metadata;
+  for (int iteration = 0; iteration < (iterations_count + 1); ++iteration) {
+    const double start_time = time();
+    run_status = session->Run(run_options, inputs, output_layer_names, {},
+                              output_layers, &run_metadata);
+    const double end_time = time();
+    if (iteration != 0) {
+      total_time += end_time - start_time;
+    }
+    if (!run_status.ok()) {
+      LOG(ERROR) << "Running model failed: " << run_status;
+      tensorflow::LogAllRegisteredKernels();
+      return run_status;
+    }
+  }
+  assert(run_metadata.has_step_stats());
+  const tensorflow::StepStats& step_stats = run_metadata.step_stats();
+  stat_summarizer->ProcessStepStats(step_stats);
+  stat_summarizer->PrintStepStats();
+
+  *average_time = total_time / iterations_count;
+  NSLog(@"Took %f seconds", *average_time);
+
+  return tensorflow::Status::OK();
+}
+
+NSString* RunInferenceOnImage() {
+  tensorflow::SessionOptions options;
+
+  tensorflow::Session* session_pointer = nullptr;
+  tensorflow::Status session_status =
+      tensorflow::NewSession(options, &session_pointer);
+  if (!session_status.ok()) {
+    std::string status_string = session_status.ToString();
+    return [NSString
+        stringWithFormat:@"Session create failed - %s", status_string.c_str()];
+  }
+  std::unique_ptr<tensorflow::Session> session(session_pointer);
+  LOG(INFO) << "Session created.";
+
+  tensorflow::GraphDef tensorflow_graph;
+  LOG(INFO) << "Graph created.";
+
+  NSString* network_path =
+      FilePathForResourceName(@"tensorflow_inception_graph", @"pb");
+  PortableReadFileToProto([network_path UTF8String], &tensorflow_graph);
+
+  LOG(INFO) << "Creating session.";
+  tensorflow::Status s = session->Create(tensorflow_graph);
+  if (!s.ok()) {
+    LOG(ERROR) << "Could not create TensorFlow Graph: " << s;
+    return @"";
+  }
+
+  // Read the label list
+  NSString* labels_path =
+      FilePathForResourceName(@"imagenet_comp_graph_label_strings", @"txt");
+  std::vector<std::string> label_strings;
+  std::ifstream t;
+  t.open([labels_path UTF8String]);
+  std::string line;
+  while (t) {
+    std::getline(t, line);
+    label_strings.push_back(line);
+  }
+  t.close();
+
+  // Read the Grace Hopper image.
+  NSString* image_path = FilePathForResourceName(@"grace_hopper", @"jpg");
+  int image_width;
+  int image_height;
+  int image_channels;
+  std::vector<tensorflow::uint8> image_data = LoadImageFromFile(
+      [image_path UTF8String], &image_width, &image_height, &image_channels);
+  const int wanted_width = 224;
+  const int wanted_height = 224;
+  const int wanted_channels = 3;
+  const float input_mean = 117.0f;
+  const float input_std = 1.0f;
+  assert(image_channels >= wanted_channels);
+  tensorflow::Tensor image_tensor(
+      tensorflow::DT_FLOAT,
+      tensorflow::TensorShape(
+          {1, wanted_height, wanted_width, wanted_channels}));
+  auto image_tensor_mapped = image_tensor.tensor<float, 4>();
+  tensorflow::uint8* in = image_data.data();
+  float* out = image_tensor_mapped.data();
+  for (int y = 0; y < wanted_height; ++y) {
+    const int in_y = (y * image_height) / wanted_height;
+    tensorflow::uint8* in_row = in + (in_y * image_width * image_channels);
+    float* out_row = out + (y * wanted_width * wanted_channels);
+    for (int x = 0; x < wanted_width; ++x) {
+      const int in_x = (x * image_width) / wanted_width;
+      tensorflow::uint8* in_pixel = in_row + (in_x * image_channels);
+      float* out_pixel = out_row + (x * wanted_channels);
+      for (int c = 0; c < wanted_channels; ++c) {
+        out_pixel[c] = (in_pixel[c] - input_mean) / input_std;
+      }
+    }
+  }
+  tensorflow::string input_layer = "input";
+  tensorflow::string output_layer = "output";
+  std::vector<tensorflow::Tensor> outputs;
+  tensorflow::StatSummarizer stat_summarizer(tensorflow_graph);
+  double average_time = 0.0;
+  BenchmarkInference(session.get(), {{input_layer, image_tensor}},
+                     {output_layer}, &outputs, &stat_summarizer, &average_time);
+  NSString* result =
+      [NSString stringWithFormat:@"Average time: %.4f seconds \n\n", average_time];
+
+  tensorflow::Tensor* output = &outputs[0];
+  const int kNumResults = 5;
+  const float kThreshold = 0.1f;
+  std::vector<std::pair<float, int>> top_results;
+  GetTopN(output->flat<float>(), kNumResults, kThreshold, &top_results);
+
+  std::stringstream ss;
+  ss.precision(3);
+  for (const auto& result : top_results) {
+    const float confidence = result.first;
+    const int index = result.second;
+
+    ss << index << " " << confidence << " ";
+
+    // Write out the result as a string
+    if (index < label_strings.size()) {
+      // just for safety: theoretically, the output is under 1000 unless there
+      // is some numerical issues leading to a wrong prediction.
+      ss << label_strings[index];
+    } else {
+      ss << "Prediction: " << index;
+    }
+
+    ss << "\n";
+  }
+
+  LOG(INFO) << "Predictions: " << ss.str();
+
+  tensorflow::string predictions = ss.str();
+  result = [NSString stringWithFormat:@"%@ - %s", result, predictions.c_str()];
+
+  return result;
+}
diff --git a/tensorflow/examples/ios/benchmark/BenchmarkViewController.xib b/tensorflow/examples/ios/benchmark/BenchmarkViewController.xib
new file mode 100644
index 0000000000..56c3708062
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/BenchmarkViewController.xib
@@ -0,0 +1,47 @@
+<?xml version="1.0" encoding="UTF-8" standalone="no"?>
+<document type="com.apple.InterfaceBuilder3.CocoaTouch.XIB" version="3.0" toolsVersion="10117" systemVersion="15G31" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES">
+    <dependencies>
+        <deployment identifier="iOS"/>
+        <plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="10085"/>
+    </dependencies>
+    <objects>
+        <placeholder placeholderIdentifier="IBFilesOwner" id="-1" userLabel="File's Owner" customClass="BenchmarkViewController">
+            <connections>
+                <outlet property="urlContentTextView" destination="quY-AK-ZCn" id="YjW-BO-1Ta"/>
+                <outlet property="urlTextField" destination="hPw-q5-vh5" id="wmc-b6-2CV"/>
+                <outlet property="view" destination="1" id="iHm-Rr-4wj"/>
+            </connections>
+        </placeholder>
+        <placeholder placeholderIdentifier="IBFirstResponder" id="-2" customClass="UIResponder"/>
+        <view contentMode="scaleToFill" id="1">
+            <rect key="frame" x="0.0" y="0.0" width="320" height="568"/>
+            <autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
+            <subviews>
+                <textView clipsSubviews="YES" contentMode="scaleToFill" fixedFrame="YES" editable="NO" text="The results of running the model will appear here." selectable="NO" translatesAutoresizingMaskIntoConstraints="NO" id="quY-AK-ZCn">
+                    <rect key="frame" x="40" y="99" width="240" height="168"/>
+                    <color key="backgroundColor" white="1" alpha="1" colorSpace="calibratedWhite"/>
+                    <fontDescription key="fontDescription" type="system" pointSize="14"/>
+                    <textInputTraits key="textInputTraits" autocapitalizationType="sentences"/>
+                </textView>
+                <button opaque="NO" contentMode="scaleToFill" fixedFrame="YES" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="AAC-Bk-PCC">
+                    <rect key="frame" x="76" y="37" width="168" height="30"/>
+                    <color key="backgroundColor" white="0.33333333333333331" alpha="1" colorSpace="calibratedWhite"/>
+                    <state key="normal" title="Benchmark Model">
+                        <color key="titleShadowColor" white="0.5" alpha="1" colorSpace="calibratedWhite"/>
+                    </state>
+                    <connections>
+                        <action selector="getUrl:" destination="-1" eventType="touchUpInside" id="mdP-nK-k9T"/>
+                    </connections>
+                </button>
+            </subviews>
+            <color key="backgroundColor" red="0.78314738357315861" green="0.79869981749999996" blue="0.56305065858222869" alpha="1" colorSpace="calibratedRGB"/>
+        </view>
+        <textField opaque="NO" clipsSubviews="YES" contentMode="scaleToFill" contentHorizontalAlignment="left" contentVerticalAlignment="center" text="http://localhost:8080" borderStyle="roundedRect" placeholder="Enter URL" minimumFontSize="17" id="hPw-q5-vh5">
+            <rect key="frame" x="0.0" y="0.0" width="280" height="30"/>
+            <autoresizingMask key="autoresizingMask" flexibleMaxX="YES" flexibleMaxY="YES"/>
+            <fontDescription key="fontDescription" type="system" pointSize="14"/>
+            <textInputTraits key="textInputTraits"/>
+            <point key="canvasLocation" x="795" y="44"/>
+        </textField>
+    </objects>
+</document>
diff --git a/tensorflow/examples/ios/benchmark/Podfile b/tensorflow/examples/ios/benchmark/Podfile
new file mode 100644
index 0000000000..e163d56e8d
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/Podfile
@@ -0,0 +1,5 @@
+platform :ios, '8.0'
+inhibit_all_warnings!
+
+target 'tf_benchmark_example'
+       pod 'TensorFlow-experimental'
diff --git a/tensorflow/examples/ios/benchmark/data/grace_hopper.jpg b/tensorflow/examples/ios/benchmark/data/grace_hopper.jpg
new file mode 100644
index 0000000000..d2a427810f
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/data/grace_hopper.jpg
diff --git a/tensorflow/examples/ios/benchmark/ios_image_load.h b/tensorflow/examples/ios/benchmark/ios_image_load.h
new file mode 100644
index 0000000000..78eaded8d7
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/ios_image_load.h
@@ -0,0 +1,27 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef TENSORFLOW_EXAMPLES_IOS_IOS_IMAGE_LOAD_H_
+#define TENSORFLOW_EXAMPLES_IOS_IOS_IMAGE_LOAD_H_
+
+#include <vector>
+
+#include "tensorflow/core/framework/types.h"
+
+std::vector<tensorflow::uint8> LoadImageFromFile(const char* file_name,
+                                                 int* out_width,
+                                                 int* out_height,
+                                                 int* out_channels);
+
+#endif  // TENSORFLOW_EXAMPLES_IOS_IOS_IMAGE_LOAD_H_
diff --git a/tensorflow/examples/ios/benchmark/ios_image_load.mm b/tensorflow/examples/ios/benchmark/ios_image_load.mm
new file mode 100644
index 0000000000..64d1ea21cf
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/ios_image_load.mm
@@ -0,0 +1,87 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "ios_image_load.h"
+
+#include <stdlib.h>
+#include <string.h>
+#include <assert.h>
+#include <stdio.h>
+
+#import <CoreImage/CoreImage.h>
+#import <ImageIO/ImageIO.h>
+
+using tensorflow::uint8;
+
+std::vector<uint8> LoadImageFromFile(const char* file_name,
+				     int* out_width, int* out_height,
+				     int* out_channels) {
+  FILE* file_handle = fopen(file_name, "rb");
+  fseek(file_handle, 0, SEEK_END);
+  const size_t bytes_in_file = ftell(file_handle);
+  fseek(file_handle, 0, SEEK_SET);
+  std::vector<uint8> file_data(bytes_in_file);
+  fread(file_data.data(), 1, bytes_in_file, file_handle);
+  fclose(file_handle);
+  CFDataRef file_data_ref = CFDataCreateWithBytesNoCopy(NULL, file_data.data(),
+						      bytes_in_file,
+						      kCFAllocatorNull);
+  CGDataProviderRef image_provider =
+    CGDataProviderCreateWithCFData(file_data_ref);
+
+  const char* suffix = strrchr(file_name, '.');
+  if (!suffix || suffix == file_name) {
+    suffix = "";
+  }
+  CGImageRef image;
+  if (strcasecmp(suffix, ".png") == 0) {
+    image = CGImageCreateWithPNGDataProvider(image_provider, NULL, true,
+					     kCGRenderingIntentDefault);
+  } else if ((strcasecmp(suffix, ".jpg") == 0) ||
+    (strcasecmp(suffix, ".jpeg") == 0)) {
+    image = CGImageCreateWithJPEGDataProvider(image_provider, NULL, true,
+					      kCGRenderingIntentDefault);
+  } else {
+    CFRelease(image_provider);
+    CFRelease(file_data_ref);
+    fprintf(stderr, "Unknown suffix for file '%s'\n", file_name);
+    *out_width = 0;
+    *out_height = 0;
+    *out_channels = 0;
+    return std::vector<uint8>();
+  }
+
+  const int width = (int)CGImageGetWidth(image);
+  const int height = (int)CGImageGetHeight(image);
+  const int channels = 4;
+  CGColorSpaceRef color_space = CGColorSpaceCreateDeviceRGB();
+  const int bytes_per_row = (width * channels);
+  const int bytes_in_image = (bytes_per_row * height);
+  std::vector<uint8> result(bytes_in_image);
+  const int bits_per_component = 8;
+  CGContextRef context = CGBitmapContextCreate(result.data(), width, height,
+    bits_per_component, bytes_per_row, color_space,
+    kCGImageAlphaPremultipliedLast | kCGBitmapByteOrder32Big);
+  CGColorSpaceRelease(color_space);
+  CGContextDrawImage(context, CGRectMake(0, 0, width, height), image);
+  CGContextRelease(context);
+  CFRelease(image);
+  CFRelease(image_provider);
+  CFRelease(file_data_ref);
+
+  *out_width = width;
+  *out_height = height;
+  *out_channels = channels;
+  return result;
+}
diff --git a/tensorflow/examples/ios/benchmark/main.mm b/tensorflow/examples/ios/benchmark/main.mm
new file mode 100644
index 0000000000..d70550a730
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/main.mm
@@ -0,0 +1,22 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <UIKit/UIKit.h>
+
+int main(int argc, char * argv[]) {
+  @autoreleasepool {
+    NSString *delegateClassName = @"AppDelegate";
+    return UIApplicationMain(argc, argv, nil, delegateClassName);
+  }
+}
diff --git a/tensorflow/examples/ios/benchmark/tf_benchmark_example.xcodeproj/project.pbxproj b/tensorflow/examples/ios/benchmark/tf_benchmark_example.xcodeproj/project.pbxproj
new file mode 100644
index 0000000000..d61b65ba61
--- /dev/null
+++ b/tensorflow/examples/ios/benchmark/tf_benchmark_example.xcodeproj/project.pbxproj
@@ -0,0 +1,388 @@
+// !$*UTF8*$!
+{
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+	objectVersion = 46;
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+
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diff --git a/tensorflow/examples/ios/camera/CameraExampleAppDelegate.h b/tensorflow/examples/ios/camera/CameraExampleAppDelegate.h
new file mode 100644
index 0000000000..0039d5e7ca
--- /dev/null
+++ b/tensorflow/examples/ios/camera/CameraExampleAppDelegate.h
@@ -0,0 +1,21 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <UIKit/UIKit.h>
+
+@interface CameraExampleAppDelegate : UIResponder<UIApplicationDelegate>
+
+@property(strong, nonatomic) UIWindow *window;
+
+@end
diff --git a/tensorflow/examples/ios/camera/CameraExampleAppDelegate.m b/tensorflow/examples/ios/camera/CameraExampleAppDelegate.m
new file mode 100644
index 0000000000..d134c2b591
--- /dev/null
+++ b/tensorflow/examples/ios/camera/CameraExampleAppDelegate.m
@@ -0,0 +1,44 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import "CameraExampleAppDelegate.h"
+
+@implementation CameraExampleAppDelegate
+
+@synthesize window = _window;
+
+- (BOOL)application:(UIApplication *)application
+    didFinishLaunchingWithOptions:(NSDictionary *)launchOptions {
+  [self.window makeKeyAndVisible];
+  return YES;
+}
+
+- (void)applicationWillResignActive:(UIApplication *)application {
+  [[UIApplication sharedApplication] setIdleTimerDisabled:NO];
+}
+
+- (void)applicationDidEnterBackground:(UIApplication *)application {
+}
+
+- (void)applicationWillEnterForeground:(UIApplication *)application {
+}
+
+- (void)applicationDidBecomeActive:(UIApplication *)application {
+  [[UIApplication sharedApplication] setIdleTimerDisabled:YES];
+}
+
+- (void)applicationWillTerminate:(UIApplication *)application {
+}
+
+@end
diff --git a/tensorflow/examples/ios/camera/CameraExampleViewController.h b/tensorflow/examples/ios/camera/CameraExampleViewController.h
new file mode 100644
index 0000000000..0aefbc6eed
--- /dev/null
+++ b/tensorflow/examples/ios/camera/CameraExampleViewController.h
@@ -0,0 +1,47 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <AVFoundation/AVFoundation.h>
+#import <UIKit/UIKit.h>
+
+#include <memory>
+#include "tensorflow/core/public/session.h"
+#include "tensorflow/core/util/memmapped_file_system.h"
+
+@interface CameraExampleViewController
+    : UIViewController<UIGestureRecognizerDelegate,
+                       AVCaptureVideoDataOutputSampleBufferDelegate> {
+  IBOutlet UIView *previewView;
+  IBOutlet UISegmentedControl *camerasControl;
+  AVCaptureVideoPreviewLayer *previewLayer;
+  AVCaptureVideoDataOutput *videoDataOutput;
+  dispatch_queue_t videoDataOutputQueue;
+  AVCaptureStillImageOutput *stillImageOutput;
+  UIView *flashView;
+  UIImage *square;
+  BOOL isUsingFrontFacingCamera;
+  AVSpeechSynthesizer *synth;
+  NSMutableDictionary *oldPredictionValues;
+  NSMutableArray *labelLayers;
+  AVCaptureSession *session;
+  std::unique_ptr<tensorflow::Session> tf_session;
+  std::unique_ptr<tensorflow::MemmappedEnv> tf_memmapped_env;
+  std::vector<std::string> labels;
+}
+@property(strong, nonatomic) CATextLayer *predictionTextLayer;
+
+- (IBAction)takePicture:(id)sender;
+- (IBAction)switchCameras:(id)sender;
+
+@end
diff --git a/tensorflow/examples/ios/camera/CameraExampleViewController.mm b/tensorflow/examples/ios/camera/CameraExampleViewController.mm
new file mode 100644
index 0000000000..d113d50ff8
--- /dev/null
+++ b/tensorflow/examples/ios/camera/CameraExampleViewController.mm
@@ -0,0 +1,621 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <AssertMacros.h>
+#import <AssetsLibrary/AssetsLibrary.h>
+#import <CoreImage/CoreImage.h>
+#import <ImageIO/ImageIO.h>
+#import "CameraExampleViewController.h"
+
+#include <sys/time.h>
+
+#include "tensorflow_utils.h"
+
+// If you have your own model, modify this to the file name, and make sure
+// you've added the file to your app resources too.
+static NSString* model_file_name = @"tensorflow_inception_graph";
+static NSString* model_file_type = @"pb";
+// This controls whether we'll be loading a plain GraphDef proto, or a
+// file created by the convert_graphdef_memmapped_format utility that wraps a
+// GraphDef and parameter file that can be mapped into memory from file to
+// reduce overall memory usage.
+const bool model_uses_memory_mapping = false;
+// If you have your own model, point this to the labels file.
+static NSString* labels_file_name = @"imagenet_comp_graph_label_strings";
+static NSString* labels_file_type = @"txt";
+// These dimensions need to match those the model was trained with.
+const int wanted_input_width = 224;
+const int wanted_input_height = 224;
+const int wanted_input_channels = 3;
+const float input_mean = 117.0f;
+const float input_std = 1.0f;
+const std::string input_layer_name = "input";
+const std::string output_layer_name = "softmax1";
+
+static void *AVCaptureStillImageIsCapturingStillImageContext =
+    &AVCaptureStillImageIsCapturingStillImageContext;
+
+@interface CameraExampleViewController (InternalMethods)
+- (void)setupAVCapture;
+- (void)teardownAVCapture;
+@end
+
+@implementation CameraExampleViewController
+
+- (void)setupAVCapture {
+  NSError *error = nil;
+
+  session = [AVCaptureSession new];
+  if ([[UIDevice currentDevice] userInterfaceIdiom] ==
+      UIUserInterfaceIdiomPhone)
+    [session setSessionPreset:AVCaptureSessionPreset640x480];
+  else
+    [session setSessionPreset:AVCaptureSessionPresetPhoto];
+
+  AVCaptureDevice *device =
+      [AVCaptureDevice defaultDeviceWithMediaType:AVMediaTypeVideo];
+  AVCaptureDeviceInput *deviceInput =
+      [AVCaptureDeviceInput deviceInputWithDevice:device error:&error];
+  assert(error == nil);
+
+  isUsingFrontFacingCamera = NO;
+  if ([session canAddInput:deviceInput]) [session addInput:deviceInput];
+
+  stillImageOutput = [AVCaptureStillImageOutput new];
+  [stillImageOutput
+      addObserver:self
+       forKeyPath:@"capturingStillImage"
+          options:NSKeyValueObservingOptionNew
+          context:(void *)(AVCaptureStillImageIsCapturingStillImageContext)];
+  if ([session canAddOutput:stillImageOutput])
+    [session addOutput:stillImageOutput];
+
+  videoDataOutput = [AVCaptureVideoDataOutput new];
+
+  NSDictionary *rgbOutputSettings = [NSDictionary
+      dictionaryWithObject:[NSNumber numberWithInt:kCMPixelFormat_32BGRA]
+                    forKey:(id)kCVPixelBufferPixelFormatTypeKey];
+  [videoDataOutput setVideoSettings:rgbOutputSettings];
+  [videoDataOutput setAlwaysDiscardsLateVideoFrames:YES];
+  videoDataOutputQueue =
+      dispatch_queue_create("VideoDataOutputQueue", DISPATCH_QUEUE_SERIAL);
+  [videoDataOutput setSampleBufferDelegate:self queue:videoDataOutputQueue];
+
+  if ([session canAddOutput:videoDataOutput])
+    [session addOutput:videoDataOutput];
+  [[videoDataOutput connectionWithMediaType:AVMediaTypeVideo] setEnabled:YES];
+
+  previewLayer = [[AVCaptureVideoPreviewLayer alloc] initWithSession:session];
+  [previewLayer setBackgroundColor:[[UIColor blackColor] CGColor]];
+  [previewLayer setVideoGravity:AVLayerVideoGravityResizeAspect];
+  CALayer *rootLayer = [previewView layer];
+  [rootLayer setMasksToBounds:YES];
+  [previewLayer setFrame:[rootLayer bounds]];
+  [rootLayer addSublayer:previewLayer];
+  [session startRunning];
+
+  if (error) {
+    NSString *title = [NSString stringWithFormat:@"Failed with error %d", (int)[error code]];
+    UIAlertController *alertController =
+        [UIAlertController alertControllerWithTitle:title
+                                            message:[error localizedDescription]
+                                     preferredStyle:UIAlertControllerStyleAlert];
+    UIAlertAction *dismiss =
+        [UIAlertAction actionWithTitle:@"Dismiss" style:UIAlertActionStyleDefault handler:nil];
+    [alertController addAction:dismiss];
+    [self presentViewController:alertController animated:YES completion:nil];
+    [self teardownAVCapture];
+  }
+}
+
+- (void)teardownAVCapture {
+  [stillImageOutput removeObserver:self forKeyPath:@"isCapturingStillImage"];
+  [previewLayer removeFromSuperlayer];
+}
+
+- (void)observeValueForKeyPath:(NSString *)keyPath
+                      ofObject:(id)object
+                        change:(NSDictionary *)change
+                       context:(void *)context {
+  if (context == AVCaptureStillImageIsCapturingStillImageContext) {
+    BOOL isCapturingStillImage =
+        [[change objectForKey:NSKeyValueChangeNewKey] boolValue];
+
+    if (isCapturingStillImage) {
+      // do flash bulb like animation
+      flashView = [[UIView alloc] initWithFrame:[previewView frame]];
+      [flashView setBackgroundColor:[UIColor whiteColor]];
+      [flashView setAlpha:0.f];
+      [[[self view] window] addSubview:flashView];
+
+      [UIView animateWithDuration:.4f
+                       animations:^{
+                         [flashView setAlpha:1.f];
+                       }];
+    } else {
+      [UIView animateWithDuration:.4f
+          animations:^{
+            [flashView setAlpha:0.f];
+          }
+          completion:^(BOOL finished) {
+            [flashView removeFromSuperview];
+            flashView = nil;
+          }];
+    }
+  }
+}
+
+- (AVCaptureVideoOrientation)avOrientationForDeviceOrientation:
+    (UIDeviceOrientation)deviceOrientation {
+  AVCaptureVideoOrientation result =
+      (AVCaptureVideoOrientation)(deviceOrientation);
+  if (deviceOrientation == UIDeviceOrientationLandscapeLeft)
+    result = AVCaptureVideoOrientationLandscapeRight;
+  else if (deviceOrientation == UIDeviceOrientationLandscapeRight)
+    result = AVCaptureVideoOrientationLandscapeLeft;
+  return result;
+}
+
+- (IBAction)takePicture:(id)sender {
+  if ([session isRunning]) {
+    [session stopRunning];
+    [sender setTitle:@"Continue" forState:UIControlStateNormal];
+
+    flashView = [[UIView alloc] initWithFrame:[previewView frame]];
+    [flashView setBackgroundColor:[UIColor whiteColor]];
+    [flashView setAlpha:0.f];
+    [[[self view] window] addSubview:flashView];
+
+    [UIView animateWithDuration:.2f
+        animations:^{
+          [flashView setAlpha:1.f];
+        }
+        completion:^(BOOL finished) {
+          [UIView animateWithDuration:.2f
+              animations:^{
+                [flashView setAlpha:0.f];
+              }
+              completion:^(BOOL finished) {
+                [flashView removeFromSuperview];
+                flashView = nil;
+              }];
+        }];
+
+  } else {
+    [session startRunning];
+    [sender setTitle:@"Freeze Frame" forState:UIControlStateNormal];
+  }
+}
+
++ (CGRect)videoPreviewBoxForGravity:(NSString *)gravity
+                          frameSize:(CGSize)frameSize
+                       apertureSize:(CGSize)apertureSize {
+  CGFloat apertureRatio = apertureSize.height / apertureSize.width;
+  CGFloat viewRatio = frameSize.width / frameSize.height;
+
+  CGSize size = CGSizeZero;
+  if ([gravity isEqualToString:AVLayerVideoGravityResizeAspectFill]) {
+    if (viewRatio > apertureRatio) {
+      size.width = frameSize.width;
+      size.height =
+          apertureSize.width * (frameSize.width / apertureSize.height);
+    } else {
+      size.width =
+          apertureSize.height * (frameSize.height / apertureSize.width);
+      size.height = frameSize.height;
+    }
+  } else if ([gravity isEqualToString:AVLayerVideoGravityResizeAspect]) {
+    if (viewRatio > apertureRatio) {
+      size.width =
+          apertureSize.height * (frameSize.height / apertureSize.width);
+      size.height = frameSize.height;
+    } else {
+      size.width = frameSize.width;
+      size.height =
+          apertureSize.width * (frameSize.width / apertureSize.height);
+    }
+  } else if ([gravity isEqualToString:AVLayerVideoGravityResize]) {
+    size.width = frameSize.width;
+    size.height = frameSize.height;
+  }
+
+  CGRect videoBox;
+  videoBox.size = size;
+  if (size.width < frameSize.width)
+    videoBox.origin.x = (frameSize.width - size.width) / 2;
+  else
+    videoBox.origin.x = (size.width - frameSize.width) / 2;
+
+  if (size.height < frameSize.height)
+    videoBox.origin.y = (frameSize.height - size.height) / 2;
+  else
+    videoBox.origin.y = (size.height - frameSize.height) / 2;
+
+  return videoBox;
+}
+
+- (void)captureOutput:(AVCaptureOutput *)captureOutput
+didOutputSampleBuffer:(CMSampleBufferRef)sampleBuffer
+       fromConnection:(AVCaptureConnection *)connection {
+  CVPixelBufferRef pixelBuffer = CMSampleBufferGetImageBuffer(sampleBuffer);
+  CFRetain(pixelBuffer);
+  [self runCNNOnFrame:pixelBuffer];
+  CFRelease(pixelBuffer);
+}
+
+- (void)runCNNOnFrame:(CVPixelBufferRef)pixelBuffer {
+  assert(pixelBuffer != NULL);
+
+  OSType sourcePixelFormat = CVPixelBufferGetPixelFormatType(pixelBuffer);
+  int doReverseChannels;
+  if (kCVPixelFormatType_32ARGB == sourcePixelFormat) {
+    doReverseChannels = 1;
+  } else if (kCVPixelFormatType_32BGRA == sourcePixelFormat) {
+    doReverseChannels = 0;
+  } else {
+    assert(false);  // Unknown source format
+  }
+
+  const int sourceRowBytes = (int)CVPixelBufferGetBytesPerRow(pixelBuffer);
+  const int image_width = (int)CVPixelBufferGetWidth(pixelBuffer);
+  const int fullHeight = (int)CVPixelBufferGetHeight(pixelBuffer);
+
+  CVPixelBufferLockFlags unlockFlags = kNilOptions;
+  CVPixelBufferLockBaseAddress(pixelBuffer, unlockFlags);
+
+  unsigned char *sourceBaseAddr =
+      (unsigned char *)(CVPixelBufferGetBaseAddress(pixelBuffer));
+  int image_height;
+  unsigned char *sourceStartAddr;
+  if (fullHeight <= image_width) {
+    image_height = fullHeight;
+    sourceStartAddr = sourceBaseAddr;
+  } else {
+    image_height = image_width;
+    const int marginY = ((fullHeight - image_width) / 2);
+    sourceStartAddr = (sourceBaseAddr + (marginY * sourceRowBytes));
+  }
+  const int image_channels = 4;
+
+  assert(image_channels >= wanted_input_channels);
+  tensorflow::Tensor image_tensor(
+      tensorflow::DT_FLOAT,
+      tensorflow::TensorShape(
+          {1, wanted_input_height, wanted_input_width, wanted_input_channels}));
+  auto image_tensor_mapped = image_tensor.tensor<float, 4>();
+  tensorflow::uint8 *in = sourceStartAddr;
+  float *out = image_tensor_mapped.data();
+  for (int y = 0; y < wanted_input_height; ++y) {
+    float *out_row = out + (y * wanted_input_width * wanted_input_channels);
+    for (int x = 0; x < wanted_input_width; ++x) {
+      const int in_x = (y * image_width) / wanted_input_width;
+      const int in_y = (x * image_height) / wanted_input_height;
+      tensorflow::uint8 *in_pixel =
+          in + (in_y * image_width * image_channels) + (in_x * image_channels);
+      float *out_pixel = out_row + (x * wanted_input_channels);
+      for (int c = 0; c < wanted_input_channels; ++c) {
+        out_pixel[c] = (in_pixel[c] - input_mean) / input_std;
+      }
+    }
+  }
+
+  CVPixelBufferUnlockBaseAddress(pixelBuffer, unlockFlags);
+
+  if (tf_session.get()) {
+    std::vector<tensorflow::Tensor> outputs;
+    tensorflow::Status run_status = tf_session->Run(
+        {{input_layer_name, image_tensor}}, {output_layer_name}, {}, &outputs);
+    if (!run_status.ok()) {
+      LOG(ERROR) << "Running model failed:" << run_status;
+    } else {
+      tensorflow::Tensor *output = &outputs[0];
+      auto predictions = output->flat<float>();
+
+      NSMutableDictionary *newValues = [NSMutableDictionary dictionary];
+      for (int index = 0; index < predictions.size(); index += 1) {
+        const float predictionValue = predictions(index);
+        if (predictionValue > 0.05f) {
+          std::string label = labels[index % predictions.size()];
+          NSString *labelObject = [NSString stringWithUTF8String:label.c_str()];
+          NSNumber *valueObject = [NSNumber numberWithFloat:predictionValue];
+          [newValues setObject:valueObject forKey:labelObject];
+        }
+      }
+      dispatch_async(dispatch_get_main_queue(), ^(void) {
+        [self setPredictionValues:newValues];
+      });
+    }
+  }
+  CVPixelBufferUnlockBaseAddress(pixelBuffer, 0);
+}
+
+- (void)dealloc {
+  [self teardownAVCapture];
+}
+
+// use front/back camera
+- (IBAction)switchCameras:(id)sender {
+  AVCaptureDevicePosition desiredPosition;
+  if (isUsingFrontFacingCamera)
+    desiredPosition = AVCaptureDevicePositionBack;
+  else
+    desiredPosition = AVCaptureDevicePositionFront;
+
+  for (AVCaptureDevice *d in
+       [AVCaptureDevice devicesWithMediaType:AVMediaTypeVideo]) {
+    if ([d position] == desiredPosition) {
+      [[previewLayer session] beginConfiguration];
+      AVCaptureDeviceInput *input =
+          [AVCaptureDeviceInput deviceInputWithDevice:d error:nil];
+      for (AVCaptureInput *oldInput in [[previewLayer session] inputs]) {
+        [[previewLayer session] removeInput:oldInput];
+      }
+      [[previewLayer session] addInput:input];
+      [[previewLayer session] commitConfiguration];
+      break;
+    }
+  }
+  isUsingFrontFacingCamera = !isUsingFrontFacingCamera;
+}
+
+- (void)didReceiveMemoryWarning {
+  [super didReceiveMemoryWarning];
+}
+
+- (void)viewDidLoad {
+  [super viewDidLoad];
+  square = [UIImage imageNamed:@"squarePNG"];
+  synth = [[AVSpeechSynthesizer alloc] init];
+  labelLayers = [[NSMutableArray alloc] init];
+  oldPredictionValues = [[NSMutableDictionary alloc] init];
+
+  tensorflow::Status load_status;
+  if (model_uses_memory_mapping) {
+    load_status = LoadMemoryMappedModel(
+        model_file_name, model_file_type, &tf_session, &tf_memmapped_env);
+  } else {
+    load_status = LoadModel(model_file_name, model_file_type, &tf_session);
+  }
+  if (!load_status.ok()) {
+    LOG(FATAL) << "Couldn't load model: " << load_status;
+  }
+
+  tensorflow::Status labels_status =
+      LoadLabels(labels_file_name, labels_file_type, &labels);
+  if (!labels_status.ok()) {
+    LOG(FATAL) << "Couldn't load labels: " << labels_status;
+  }
+  [self setupAVCapture];
+}
+
+- (void)viewDidUnload {
+  [super viewDidUnload];
+}
+
+- (void)viewWillAppear:(BOOL)animated {
+  [super viewWillAppear:animated];
+}
+
+- (void)viewDidAppear:(BOOL)animated {
+  [super viewDidAppear:animated];
+}
+
+- (void)viewWillDisappear:(BOOL)animated {
+  [super viewWillDisappear:animated];
+}
+
+- (void)viewDidDisappear:(BOOL)animated {
+  [super viewDidDisappear:animated];
+}
+
+- (BOOL)shouldAutorotateToInterfaceOrientation:
+    (UIInterfaceOrientation)interfaceOrientation {
+  return (interfaceOrientation == UIInterfaceOrientationPortrait);
+}
+
+- (BOOL)prefersStatusBarHidden {
+  return YES;
+}
+
+- (void)setPredictionValues:(NSDictionary *)newValues {
+  const float decayValue = 0.75f;
+  const float updateValue = 0.25f;
+  const float minimumThreshold = 0.01f;
+
+  NSMutableDictionary *decayedPredictionValues =
+      [[NSMutableDictionary alloc] init];
+  for (NSString *label in oldPredictionValues) {
+    NSNumber *oldPredictionValueObject =
+        [oldPredictionValues objectForKey:label];
+    const float oldPredictionValue = [oldPredictionValueObject floatValue];
+    const float decayedPredictionValue = (oldPredictionValue * decayValue);
+    if (decayedPredictionValue > minimumThreshold) {
+      NSNumber *decayedPredictionValueObject =
+          [NSNumber numberWithFloat:decayedPredictionValue];
+      [decayedPredictionValues setObject:decayedPredictionValueObject
+                                  forKey:label];
+    }
+  }
+  oldPredictionValues = decayedPredictionValues;
+
+  for (NSString *label in newValues) {
+    NSNumber *newPredictionValueObject = [newValues objectForKey:label];
+    NSNumber *oldPredictionValueObject =
+        [oldPredictionValues objectForKey:label];
+    if (!oldPredictionValueObject) {
+      oldPredictionValueObject = [NSNumber numberWithFloat:0.0f];
+    }
+    const float newPredictionValue = [newPredictionValueObject floatValue];
+    const float oldPredictionValue = [oldPredictionValueObject floatValue];
+    const float updatedPredictionValue =
+        (oldPredictionValue + (newPredictionValue * updateValue));
+    NSNumber *updatedPredictionValueObject =
+        [NSNumber numberWithFloat:updatedPredictionValue];
+    [oldPredictionValues setObject:updatedPredictionValueObject forKey:label];
+  }
+  NSArray *candidateLabels = [NSMutableArray array];
+  for (NSString *label in oldPredictionValues) {
+    NSNumber *oldPredictionValueObject =
+        [oldPredictionValues objectForKey:label];
+    const float oldPredictionValue = [oldPredictionValueObject floatValue];
+    if (oldPredictionValue > 0.05f) {
+      NSDictionary *entry = @{
+        @"label" : label,
+        @"value" : oldPredictionValueObject
+      };
+      candidateLabels = [candidateLabels arrayByAddingObject:entry];
+    }
+  }
+  NSSortDescriptor *sort =
+      [NSSortDescriptor sortDescriptorWithKey:@"value" ascending:NO];
+  NSArray *sortedLabels = [candidateLabels
+      sortedArrayUsingDescriptors:[NSArray arrayWithObject:sort]];
+
+  const float leftMargin = 10.0f;
+  const float topMargin = 10.0f;
+
+  const float valueWidth = 48.0f;
+  const float valueHeight = 26.0f;
+
+  const float labelWidth = 246.0f;
+  const float labelHeight = 26.0f;
+
+  const float labelMarginX = 5.0f;
+  const float labelMarginY = 5.0f;
+
+  [self removeAllLabelLayers];
+
+  int labelCount = 0;
+  for (NSDictionary *entry in sortedLabels) {
+    NSString *label = [entry objectForKey:@"label"];
+    NSNumber *valueObject = [entry objectForKey:@"value"];
+    const float value = [valueObject floatValue];
+
+    const float originY =
+        (topMargin + ((labelHeight + labelMarginY) * labelCount));
+
+    const int valuePercentage = (int)roundf(value * 100.0f);
+
+    const float valueOriginX = leftMargin;
+    NSString *valueText = [NSString stringWithFormat:@"%d%%", valuePercentage];
+
+    [self addLabelLayerWithText:valueText
+                        originX:valueOriginX
+                        originY:originY
+                          width:valueWidth
+                         height:valueHeight
+                      alignment:kCAAlignmentRight];
+
+    const float labelOriginX = (leftMargin + valueWidth + labelMarginX);
+
+    [self addLabelLayerWithText:[label capitalizedString]
+                        originX:labelOriginX
+                        originY:originY
+                          width:labelWidth
+                         height:labelHeight
+                      alignment:kCAAlignmentLeft];
+
+    if ((labelCount == 0) && (value > 0.5f)) {
+      [self speak:[label capitalizedString]];
+    }
+
+    labelCount += 1;
+    if (labelCount > 4) {
+      break;
+    }
+  }
+}
+
+- (void)removeAllLabelLayers {
+  for (CATextLayer *layer in labelLayers) {
+    [layer removeFromSuperlayer];
+  }
+  [labelLayers removeAllObjects];
+}
+
+- (void)addLabelLayerWithText:(NSString *)text
+                      originX:(float)originX
+                      originY:(float)originY
+                        width:(float)width
+                       height:(float)height
+                    alignment:(NSString *)alignment {
+  CFTypeRef font = (CFTypeRef) @"Menlo-Regular";
+  const float fontSize = 20.0f;
+
+  const float marginSizeX = 5.0f;
+  const float marginSizeY = 2.0f;
+
+  const CGRect backgroundBounds = CGRectMake(originX, originY, width, height);
+
+  const CGRect textBounds =
+      CGRectMake((originX + marginSizeX), (originY + marginSizeY),
+                 (width - (marginSizeX * 2)), (height - (marginSizeY * 2)));
+
+  CATextLayer *background = [CATextLayer layer];
+  [background setBackgroundColor:[UIColor blackColor].CGColor];
+  [background setOpacity:0.5f];
+  [background setFrame:backgroundBounds];
+  background.cornerRadius = 5.0f;
+
+  [[self.view layer] addSublayer:background];
+  [labelLayers addObject:background];
+
+  CATextLayer *layer = [CATextLayer layer];
+  [layer setForegroundColor:[UIColor whiteColor].CGColor];
+  [layer setFrame:textBounds];
+  [layer setAlignmentMode:alignment];
+  [layer setWrapped:YES];
+  [layer setFont:font];
+  [layer setFontSize:fontSize];
+  layer.contentsScale = [[UIScreen mainScreen] scale];
+  [layer setString:text];
+
+  [[self.view layer] addSublayer:layer];
+  [labelLayers addObject:layer];
+}
+
+- (void)setPredictionText:(NSString *)text withDuration:(float)duration {
+  if (duration > 0.0) {
+    CABasicAnimation *colorAnimation =
+        [CABasicAnimation animationWithKeyPath:@"foregroundColor"];
+    colorAnimation.duration = duration;
+    colorAnimation.fillMode = kCAFillModeForwards;
+    colorAnimation.removedOnCompletion = NO;
+    colorAnimation.fromValue = (id)[UIColor darkGrayColor].CGColor;
+    colorAnimation.toValue = (id)[UIColor whiteColor].CGColor;
+    colorAnimation.timingFunction =
+        [CAMediaTimingFunction functionWithName:kCAMediaTimingFunctionLinear];
+    [self.predictionTextLayer addAnimation:colorAnimation
+                                    forKey:@"colorAnimation"];
+  } else {
+    self.predictionTextLayer.foregroundColor = [UIColor whiteColor].CGColor;
+  }
+
+  [self.predictionTextLayer removeFromSuperlayer];
+  [[self.view layer] addSublayer:self.predictionTextLayer];
+  [self.predictionTextLayer setString:text];
+}
+
+- (void)speak:(NSString *)words {
+  if ([synth isSpeaking]) {
+    return;
+  }
+  AVSpeechUtterance *utterance =
+      [AVSpeechUtterance speechUtteranceWithString:words];
+  utterance.voice = [AVSpeechSynthesisVoice voiceWithLanguage:@"en-US"];
+  utterance.rate = 0.75 * AVSpeechUtteranceDefaultSpeechRate;
+  [synth speakUtterance:utterance];
+}
+
+@end
diff --git a/tensorflow/examples/ios/camera/Info.plist b/tensorflow/examples/ios/camera/Info.plist
new file mode 100644
index 0000000000..772fb38dcc
--- /dev/null
+++ b/tensorflow/examples/ios/camera/Info.plist
@@ -0,0 +1,44 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
+<plist version="1.0">
+<dict>
+	<key>CFBundleDevelopmentRegion</key>
+	<string>en</string>
+	<key>CFBundleDisplayName</key>
+	<string>tf_camera_example</string>
+	<key>CFBundleExecutable</key>
+	<string>${EXECUTABLE_NAME}</string>
+	<key>CFBundleIdentifier</key>
+	<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
+	<key>CFBundleInfoDictionaryVersion</key>
+	<string>6.0</string>
+	<key>CFBundleName</key>
+	<string>${PRODUCT_NAME}</string>
+	<key>CFBundlePackageType</key>
+	<string>APPL</string>
+	<key>CFBundleShortVersionString</key>
+	<string>1.0</string>
+	<key>CFBundleSignature</key>
+	<string>????</string>
+	<key>CFBundleVersion</key>
+	<string>1.0</string>
+	<key>LSRequiresIPhoneOS</key>
+	<true/>
+	<key>NSCameraUsageDescription</key>
+	<string>Capture images to detect object</string>
+	<key>UIMainStoryboardFile</key>
+	<string>MainStoryboard_iPhone</string>
+	<key>UIRequiresFullScreen</key>
+	<true/>
+	<key>UIStatusBarHidden</key>
+	<true/>
+	<key>UISupportedInterfaceOrientations</key>
+	<array>
+		<string>UIInterfaceOrientationPortrait</string>
+	</array>
+	<key>UISupportedInterfaceOrientations~ipad</key>
+	<array>
+		<string>UIInterfaceOrientationPortrait</string>
+	</array>
+</dict>
+</plist>
diff --git a/tensorflow/examples/ios/camera/MainStoryboard_iPhone.storyboard b/tensorflow/examples/ios/camera/MainStoryboard_iPhone.storyboard
new file mode 100644
index 0000000000..0f10a22e41
--- /dev/null
+++ b/tensorflow/examples/ios/camera/MainStoryboard_iPhone.storyboard
@@ -0,0 +1,46 @@
+<?xml version="1.0" encoding="UTF-8" standalone="no"?>
+<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="9531" systemVersion="15E65" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" initialViewController="2">
+    <dependencies>
+        <deployment identifier="iOS"/>
+        <plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="9529"/>
+    </dependencies>
+    <scenes>
+        <!--Camera Example View Controller-->
+        <scene sceneID="5">
+            <objects>
+                <viewController id="2" customClass="CameraExampleViewController" sceneMemberID="viewController">
+                    <view key="view" contentMode="scaleToFill" id="3">
+                        <rect key="frame" x="0.0" y="0.0" width="320" height="568"/>
+                        <autoresizingMask key="autoresizingMask" flexibleMaxX="YES" flexibleMaxY="YES"/>
+                        <subviews>
+                            <view contentMode="scaleToFill" id="12">
+                                <rect key="frame" x="0.0" y="0.0" width="320" height="522"/>
+                                <autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
+                                <color key="backgroundColor" white="1" alpha="1" colorSpace="custom" customColorSpace="calibratedWhite"/>
+                                <gestureRecognizers/>
+                            </view>
+                            <button opaque="NO" contentMode="scaleToFill" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" lineBreakMode="middleTruncation" id="iD8-yH-eWH">
+                                <rect key="frame" x="0.0" y="454" width="320" height="33"/>
+                                <autoresizingMask key="autoresizingMask" flexibleMaxX="YES" flexibleMaxY="YES"/>
+                                <color key="backgroundColor" red="0.0" green="0.0" blue="0.0" alpha="1" colorSpace="calibratedRGB"/>
+                                <fontDescription key="fontDescription" name="Menlo-Regular" family="Menlo" pointSize="20"/>
+                                <state key="normal" title="Freeze Frame">
+                                    <color key="titleColor" white="1" alpha="1" colorSpace="calibratedWhite"/>
+                                    <color key="titleShadowColor" white="0.5" alpha="1" colorSpace="calibratedWhite"/>
+                                </state>
+                                <connections>
+                                    <action selector="takePicture:" destination="2" eventType="touchUpInside" id="BTy-7E-XUS"/>
+                                </connections>
+                            </button>
+                        </subviews>
+                        <color key="backgroundColor" red="0.0" green="0.0" blue="0.0" alpha="1" colorSpace="calibratedRGB"/>
+                    </view>
+                    <connections>
+                        <outlet property="previewView" destination="12" id="13"/>
+                    </connections>
+                </viewController>
+                <placeholder placeholderIdentifier="IBFirstResponder" id="4" sceneMemberID="firstResponder"/>
+            </objects>
+        </scene>
+    </scenes>
+</document>
diff --git a/tensorflow/examples/ios/camera/Podfile b/tensorflow/examples/ios/camera/Podfile
new file mode 100644
index 0000000000..117828f071
--- /dev/null
+++ b/tensorflow/examples/ios/camera/Podfile
@@ -0,0 +1,5 @@
+platform :ios, '8.0'
+inhibit_all_warnings!
+
+target 'tf_camera_example'
+       pod 'TensorFlow-experimental'
diff --git a/tensorflow/examples/ios/camera/data/grace_hopper.jpg b/tensorflow/examples/ios/camera/data/grace_hopper.jpg
new file mode 100644
index 0000000000..d2a427810f
--- /dev/null
+++ b/tensorflow/examples/ios/camera/data/grace_hopper.jpg
diff --git a/tensorflow/examples/ios/camera/ios_image_load.h b/tensorflow/examples/ios/camera/ios_image_load.h
new file mode 100644
index 0000000000..87a847e145
--- /dev/null
+++ b/tensorflow/examples/ios/camera/ios_image_load.h
@@ -0,0 +1,27 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef TENSORFLOW_CONTRIB_IOS_EXAMPLES_CAMERA_IMAGE_LOAD_H_
+#define TENSORFLOW_CONTRIB_IOS_EXAMPLES_CAMERA_IMAGE_LOAD_H_
+
+#include <vector>
+
+#include "tensorflow/core/framework/types.h"
+
+std::vector<tensorflow::uint8> LoadImageFromFile(const char* file_name,
+						 int* out_width,
+						 int* out_height,
+						 int* out_channels);
+
+#endif  // TENSORFLOW_CONTRIB_IOS_EXAMPLES_CAMERA_IMAGE_LOAD_H_
diff --git a/tensorflow/examples/ios/camera/ios_image_load.mm b/tensorflow/examples/ios/camera/ios_image_load.mm
new file mode 100644
index 0000000000..64d1ea21cf
--- /dev/null
+++ b/tensorflow/examples/ios/camera/ios_image_load.mm
@@ -0,0 +1,87 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "ios_image_load.h"
+
+#include <stdlib.h>
+#include <string.h>
+#include <assert.h>
+#include <stdio.h>
+
+#import <CoreImage/CoreImage.h>
+#import <ImageIO/ImageIO.h>
+
+using tensorflow::uint8;
+
+std::vector<uint8> LoadImageFromFile(const char* file_name,
+				     int* out_width, int* out_height,
+				     int* out_channels) {
+  FILE* file_handle = fopen(file_name, "rb");
+  fseek(file_handle, 0, SEEK_END);
+  const size_t bytes_in_file = ftell(file_handle);
+  fseek(file_handle, 0, SEEK_SET);
+  std::vector<uint8> file_data(bytes_in_file);
+  fread(file_data.data(), 1, bytes_in_file, file_handle);
+  fclose(file_handle);
+  CFDataRef file_data_ref = CFDataCreateWithBytesNoCopy(NULL, file_data.data(),
+						      bytes_in_file,
+						      kCFAllocatorNull);
+  CGDataProviderRef image_provider =
+    CGDataProviderCreateWithCFData(file_data_ref);
+
+  const char* suffix = strrchr(file_name, '.');
+  if (!suffix || suffix == file_name) {
+    suffix = "";
+  }
+  CGImageRef image;
+  if (strcasecmp(suffix, ".png") == 0) {
+    image = CGImageCreateWithPNGDataProvider(image_provider, NULL, true,
+					     kCGRenderingIntentDefault);
+  } else if ((strcasecmp(suffix, ".jpg") == 0) ||
+    (strcasecmp(suffix, ".jpeg") == 0)) {
+    image = CGImageCreateWithJPEGDataProvider(image_provider, NULL, true,
+					      kCGRenderingIntentDefault);
+  } else {
+    CFRelease(image_provider);
+    CFRelease(file_data_ref);
+    fprintf(stderr, "Unknown suffix for file '%s'\n", file_name);
+    *out_width = 0;
+    *out_height = 0;
+    *out_channels = 0;
+    return std::vector<uint8>();
+  }
+
+  const int width = (int)CGImageGetWidth(image);
+  const int height = (int)CGImageGetHeight(image);
+  const int channels = 4;
+  CGColorSpaceRef color_space = CGColorSpaceCreateDeviceRGB();
+  const int bytes_per_row = (width * channels);
+  const int bytes_in_image = (bytes_per_row * height);
+  std::vector<uint8> result(bytes_in_image);
+  const int bits_per_component = 8;
+  CGContextRef context = CGBitmapContextCreate(result.data(), width, height,
+    bits_per_component, bytes_per_row, color_space,
+    kCGImageAlphaPremultipliedLast | kCGBitmapByteOrder32Big);
+  CGColorSpaceRelease(color_space);
+  CGContextDrawImage(context, CGRectMake(0, 0, width, height), image);
+  CGContextRelease(context);
+  CFRelease(image);
+  CFRelease(image_provider);
+  CFRelease(file_data_ref);
+
+  *out_width = width;
+  *out_height = height;
+  *out_channels = channels;
+  return result;
+}
diff --git a/tensorflow/examples/ios/camera/main.mm b/tensorflow/examples/ios/camera/main.mm
new file mode 100644
index 0000000000..42eff697ef
--- /dev/null
+++ b/tensorflow/examples/ios/camera/main.mm
@@ -0,0 +1,27 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <UIKit/UIKit.h>
+
+#import "CameraExampleAppDelegate.h"
+
+int main(int argc, char *argv[]) {
+  int retVal = 0;
+
+  @autoreleasepool {
+    retVal = UIApplicationMain(
+        argc, argv, nil, NSStringFromClass([CameraExampleAppDelegate class]));
+  }
+  return retVal;
+}
diff --git a/tensorflow/examples/ios/camera/tensorflow_utils.h b/tensorflow/examples/ios/camera/tensorflow_utils.h
new file mode 100644
index 0000000000..78bdb82aae
--- /dev/null
+++ b/tensorflow/examples/ios/camera/tensorflow_utils.h
@@ -0,0 +1,52 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef TENSORFLOW_CONTRIB_IOS_EXAMPLES_CAMERA_TENSORFLOW_UTILS_H_
+#define TENSORFLOW_CONTRIB_IOS_EXAMPLES_CAMERA_TENSORFLOW_UTILS_H_
+
+#include <memory>
+#include <vector>
+
+#include "tensorflow/core/public/session.h"
+#include "tensorflow/core/util/memmapped_file_system.h"
+#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
+
+// Reads a serialized GraphDef protobuf file from the bundle, typically
+// created with the freeze_graph script. Populates the session argument with a
+// Session object that has the model loaded.
+tensorflow::Status LoadModel(NSString* file_name, NSString* file_type,
+                             std::unique_ptr<tensorflow::Session>* session);
+
+// Loads a model from a file that has been created using the
+// convert_graphdef_memmapped_format tool. This bundles together a GraphDef
+// proto together with a file that can be memory-mapped, containing the weight
+// parameters for the model. This is useful because it reduces the overall
+// memory pressure, since the read-only parameter regions can be easily paged
+// out and don't count toward memory limits on iOS.
+tensorflow::Status LoadMemoryMappedModel(
+    NSString* file_name, NSString* file_type,
+    std::unique_ptr<tensorflow::Session>* session,
+    std::unique_ptr<tensorflow::MemmappedEnv>* memmapped_env);
+
+// Takes a text file with a single label on each line, and returns a list.
+tensorflow::Status LoadLabels(NSString* file_name, NSString* file_type,
+                              std::vector<std::string>* label_strings);
+
+// Sorts the results from a model execution, and returns the highest scoring.
+void GetTopN(const Eigen::TensorMap<Eigen::Tensor<float, 1, Eigen::RowMajor>,
+                                    Eigen::Aligned>& prediction,
+             const int num_results, const float threshold,
+             std::vector<std::pair<float, int> >* top_results);
+
+#endif  // TENSORFLOW_CONTRIB_IOS_EXAMPLES_CAMERA_TENSORFLOW_UTILS_H_
diff --git a/tensorflow/examples/ios/camera/tensorflow_utils.mm b/tensorflow/examples/ios/camera/tensorflow_utils.mm
new file mode 100644
index 0000000000..56d1e53081
--- /dev/null
+++ b/tensorflow/examples/ios/camera/tensorflow_utils.mm
@@ -0,0 +1,219 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <Foundation/Foundation.h>
+
+#include "tensorflow_utils.h"
+
+#include <pthread.h>
+#include <unistd.h>
+#include <fstream>
+#include <queue>
+#include <sstream>
+#include <string>
+
+namespace {
+
+// Helper class used to load protobufs efficiently.
+class IfstreamInputStream : public ::google::protobuf::io::CopyingInputStream {
+ public:
+  explicit IfstreamInputStream(const std::string& file_name)
+      : ifs_(file_name.c_str(), std::ios::in | std::ios::binary) {}
+  ~IfstreamInputStream() { ifs_.close(); }
+
+  int Read(void* buffer, int size) {
+    if (!ifs_) {
+      return -1;
+    }
+    ifs_.read(static_cast<char*>(buffer), size);
+    return ifs_.gcount();
+  }
+
+ private:
+  std::ifstream ifs_;
+};
+}  // namespace
+
+// Returns the top N confidence values over threshold in the provided vector,
+// sorted by confidence in descending order.
+void GetTopN(const Eigen::TensorMap<Eigen::Tensor<float, 1, Eigen::RowMajor>,
+                                    Eigen::Aligned>& prediction,
+             const int num_results, const float threshold,
+             std::vector<std::pair<float, int> >* top_results) {
+  // Will contain top N results in ascending order.
+  std::priority_queue<std::pair<float, int>,
+                      std::vector<std::pair<float, int> >,
+                      std::greater<std::pair<float, int> > >
+      top_result_pq;
+
+  const int count = prediction.size();
+  for (int i = 0; i < count; ++i) {
+    const float value = prediction(i);
+
+    // Only add it if it beats the threshold and has a chance at being in
+    // the top N.
+    if (value < threshold) {
+      continue;
+    }
+
+    top_result_pq.push(std::pair<float, int>(value, i));
+
+    // If at capacity, kick the smallest value out.
+    if (top_result_pq.size() > num_results) {
+      top_result_pq.pop();
+    }
+  }
+
+  // Copy to output vector and reverse into descending order.
+  while (!top_result_pq.empty()) {
+    top_results->push_back(top_result_pq.top());
+    top_result_pq.pop();
+  }
+  std::reverse(top_results->begin(), top_results->end());
+}
+
+bool PortableReadFileToProto(const std::string& file_name,
+                             ::google::protobuf::MessageLite* proto) {
+  ::google::protobuf::io::CopyingInputStreamAdaptor stream(
+      new IfstreamInputStream(file_name));
+  stream.SetOwnsCopyingStream(true);
+  ::google::protobuf::io::CodedInputStream coded_stream(&stream);
+  // Total bytes hard limit / warning limit are set to 1GB and 512MB
+  // respectively.
+  coded_stream.SetTotalBytesLimit(1024LL << 20, 512LL << 20);
+  return proto->ParseFromCodedStream(&coded_stream);
+}
+
+NSString* FilePathForResourceName(NSString* name, NSString* extension) {
+  NSString* file_path =
+      [[NSBundle mainBundle] pathForResource:name ofType:extension];
+  if (file_path == NULL) {
+    LOG(FATAL) << "Couldn't find '" << [name UTF8String] << "."
+               << [extension UTF8String] << "' in bundle.";
+    return nullptr;
+  }
+  return file_path;
+}
+
+tensorflow::Status LoadModel(NSString* file_name, NSString* file_type,
+                             std::unique_ptr<tensorflow::Session>* session) {
+  tensorflow::SessionOptions options;
+
+  tensorflow::Session* session_pointer = nullptr;
+  tensorflow::Status session_status =
+      tensorflow::NewSession(options, &session_pointer);
+  if (!session_status.ok()) {
+    LOG(ERROR) << "Could not create TensorFlow Session: " << session_status;
+    return session_status;
+  }
+  session->reset(session_pointer);
+
+  tensorflow::GraphDef tensorflow_graph;
+
+  NSString* model_path = FilePathForResourceName(file_name, file_type);
+  if (!model_path) {
+    LOG(ERROR) << "Failed to find model proto at" << [file_name UTF8String]
+               << [file_type UTF8String];
+    return tensorflow::errors::NotFound([file_name UTF8String],
+                                        [file_type UTF8String]);
+  }
+  const bool read_proto_succeeded =
+      PortableReadFileToProto([model_path UTF8String], &tensorflow_graph);
+  if (!read_proto_succeeded) {
+    LOG(ERROR) << "Failed to load model proto from" << [model_path UTF8String];
+    return tensorflow::errors::NotFound([model_path UTF8String]);
+  }
+
+  tensorflow::Status create_status = (*session)->Create(tensorflow_graph);
+  if (!create_status.ok()) {
+    LOG(ERROR) << "Could not create TensorFlow Graph: " << create_status;
+    return create_status;
+  }
+
+  return tensorflow::Status::OK();
+}
+
+tensorflow::Status LoadMemoryMappedModel(
+    NSString* file_name, NSString* file_type,
+    std::unique_ptr<tensorflow::Session>* session,
+    std::unique_ptr<tensorflow::MemmappedEnv>* memmapped_env) {
+  NSString* network_path = FilePathForResourceName(file_name, file_type);
+  memmapped_env->reset(
+      new tensorflow::MemmappedEnv(tensorflow::Env::Default()));
+  tensorflow::Status mmap_status =
+      (memmapped_env->get())->InitializeFromFile([network_path UTF8String]);
+  if (!mmap_status.ok()) {
+    LOG(ERROR) << "MMap failed with " << mmap_status.error_message();
+    return mmap_status;
+  }
+
+  tensorflow::GraphDef tensorflow_graph;
+  tensorflow::Status load_graph_status = ReadBinaryProto(
+      memmapped_env->get(),
+      tensorflow::MemmappedFileSystem::kMemmappedPackageDefaultGraphDef,
+      &tensorflow_graph);
+  if (!load_graph_status.ok()) {
+    LOG(ERROR) << "MMap load graph failed with "
+               << load_graph_status.error_message();
+    return load_graph_status;
+  }
+
+  tensorflow::SessionOptions options;
+  // Disable optimizations on this graph so that constant folding doesn't
+  // increase the memory footprint by creating new constant copies of the weight
+  // parameters.
+  options.config.mutable_graph_options()
+      ->mutable_optimizer_options()
+      ->set_opt_level(::tensorflow::OptimizerOptions::L0);
+  options.env = memmapped_env->get();
+
+  tensorflow::Session* session_pointer = nullptr;
+  tensorflow::Status session_status =
+      tensorflow::NewSession(options, &session_pointer);
+  if (!session_status.ok()) {
+    LOG(ERROR) << "Could not create TensorFlow Session: " << session_status;
+    return session_status;
+  }
+
+  tensorflow::Status create_status = session_pointer->Create(tensorflow_graph);
+  if (!create_status.ok()) {
+    LOG(ERROR) << "Could not create TensorFlow Graph: " << create_status;
+    return create_status;
+  }
+
+  session->reset(session_pointer);
+
+  return tensorflow::Status::OK();
+}
+
+tensorflow::Status LoadLabels(NSString* file_name, NSString* file_type,
+                              std::vector<std::string>* label_strings) {
+  // Read the label list
+  NSString* labels_path = FilePathForResourceName(file_name, file_type);
+  if (!labels_path) {
+    LOG(ERROR) << "Failed to find model proto at" << [file_name UTF8String]
+               << [file_type UTF8String];
+    return tensorflow::errors::NotFound([file_name UTF8String],
+                                        [file_type UTF8String]);
+  }
+  std::ifstream t;
+  t.open([labels_path UTF8String]);
+  std::string line;
+  while (t) {
+    std::getline(t, line);
+    label_strings->push_back(line);
+  }
+  t.close();
+  return tensorflow::Status::OK();
+}
diff --git a/tensorflow/examples/ios/camera/tf_camera_example.xcodeproj/project.pbxproj b/tensorflow/examples/ios/camera/tf_camera_example.xcodeproj/project.pbxproj
new file mode 100644
index 0000000000..ee9fe57c79
--- /dev/null
+++ b/tensorflow/examples/ios/camera/tf_camera_example.xcodeproj/project.pbxproj
@@ -0,0 +1,412 @@
+// !$*UTF8*$!
+{
+	archiveVersion = 1;
+	classes = {
+	};
+	objectVersion = 46;
+	objects = {
+
+/* Begin PBXBuildFile section */
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+			);
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+}
diff --git a/tensorflow/examples/ios/simple/AppDelegate.h b/tensorflow/examples/ios/simple/AppDelegate.h
new file mode 100644
index 0000000000..75b1f1da38
--- /dev/null
+++ b/tensorflow/examples/ios/simple/AppDelegate.h
@@ -0,0 +1,21 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <UIKit/UIKit.h>
+
+@interface AppDelegate : UIResponder <UIApplicationDelegate>
+
+@property (strong, nonatomic) UIWindow *window;
+
+@end
diff --git a/tensorflow/examples/ios/simple/AppDelegate.mm b/tensorflow/examples/ios/simple/AppDelegate.mm
new file mode 100644
index 0000000000..1e808eb976
--- /dev/null
+++ b/tensorflow/examples/ios/simple/AppDelegate.mm
@@ -0,0 +1,44 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import "AppDelegate.h"
+
+#import "RunModelViewController.h"
+
+@implementation AppDelegate
+
+- (BOOL)application:(UIApplication *)application
+    didFinishLaunchingWithOptions:(NSDictionary *)launchOptions {
+
+  UITabBarController *bar = [[UITabBarController alloc] init];
+  [bar setViewControllers:
+      @[[[RunModelViewController alloc] init]]];
+  bar.selectedIndex = 0;
+  self.window = [[UIWindow alloc] initWithFrame:[[UIScreen mainScreen] bounds]];
+  self.window.rootViewController = bar;
+  [self.window makeKeyAndVisible];
+  return YES;
+}
+
+- (void)applicationWillResignActive:(UIApplication *)application {}
+
+- (void)applicationDidEnterBackground:(UIApplication *)application {}
+
+- (void)applicationWillEnterForeground:(UIApplication *)application {}
+
+- (void)applicationDidBecomeActive:(UIApplication *)application {}
+
+- (void)applicationWillTerminate:(UIApplication *)application {}
+
+@end
diff --git a/tensorflow/examples/ios/simple/Podfile b/tensorflow/examples/ios/simple/Podfile
new file mode 100644
index 0000000000..1740ad6457
--- /dev/null
+++ b/tensorflow/examples/ios/simple/Podfile
@@ -0,0 +1,5 @@
+platform :ios, '8.0'
+inhibit_all_warnings!
+
+target 'tf_simple_example'
+       pod 'TensorFlow-experimental'
diff --git a/tensorflow/examples/ios/simple/RunModel-Info.plist b/tensorflow/examples/ios/simple/RunModel-Info.plist
new file mode 100644
index 0000000000..d0a8742456
--- /dev/null
+++ b/tensorflow/examples/ios/simple/RunModel-Info.plist
@@ -0,0 +1,47 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
+<plist version="1.0">
+<dict>
+	<key>CFBundleDevelopmentRegion</key>
+	<string>en</string>
+	<key>CFBundleDisplayName</key>
+	<string>tf_simple_example</string>
+	<key>CFBundleExecutable</key>
+	<string>tf_simple_example</string>
+	<key>CFBundleIdentifier</key>
+	<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
+	<key>CFBundleInfoDictionaryVersion</key>
+	<string>6.0</string>
+	<key>CFBundleName</key>
+	<string>ios-app</string>
+	<key>CFBundlePackageType</key>
+	<string>APPL</string>
+	<key>CFBundleShortVersionString</key>
+	<string>1.0</string>
+	<key>CFBundleSignature</key>
+	<string>????</string>
+	<key>CFBundleVersion</key>
+	<string>1.0</string>
+	<key>LSRequiresIPhoneOS</key>
+	<true/>
+	<key>UILaunchStoryboardName</key>
+	<string>RunModelViewController</string>
+	<key>UIRequiredDeviceCapabilities</key>
+	<array>
+		<string>armv7</string>
+	</array>
+	<key>UISupportedInterfaceOrientations</key>
+	<array>
+		<string>UIInterfaceOrientationPortrait</string>
+		<string>UIInterfaceOrientationLandscapeLeft</string>
+		<string>UIInterfaceOrientationLandscapeRight</string>
+	</array>
+	<key>UISupportedInterfaceOrientations~ipad</key>
+	<array>
+		<string>UIInterfaceOrientationPortrait</string>
+		<string>UIInterfaceOrientationPortraitUpsideDown</string>
+		<string>UIInterfaceOrientationLandscapeLeft</string>
+		<string>UIInterfaceOrientationLandscapeRight</string>
+	</array>
+</dict>
+</plist>
diff --git a/tensorflow/examples/ios/simple/RunModelViewController.h b/tensorflow/examples/ios/simple/RunModelViewController.h
new file mode 100644
index 0000000000..4e1a83ccf5
--- /dev/null
+++ b/tensorflow/examples/ios/simple/RunModelViewController.h
@@ -0,0 +1,24 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <UIKit/UIKit.h>
+
+@interface RunModelViewController : UIViewController
+
+- (IBAction)getUrl:(id)sender;
+
+@property (weak, nonatomic) IBOutlet UITextView *urlContentTextView;
+@property (weak, nonatomic) IBOutlet UITextField *urlTextField;
+
+@end
diff --git a/tensorflow/examples/ios/simple/RunModelViewController.mm b/tensorflow/examples/ios/simple/RunModelViewController.mm
new file mode 100644
index 0000000000..c8ccb5c77b
--- /dev/null
+++ b/tensorflow/examples/ios/simple/RunModelViewController.mm
@@ -0,0 +1,253 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import "RunModelViewController.h"
+
+#include <fstream>
+#include <pthread.h>
+#include <unistd.h>
+#include <queue>
+#include <sstream>
+#include <string>
+
+#include "tensorflow/core/framework/op_kernel.h"
+#include "tensorflow/core/public/session.h"
+
+#include "ios_image_load.h"
+
+NSString* RunInferenceOnImage();
+
+namespace {
+class IfstreamInputStream : public ::google::protobuf::io::CopyingInputStream {
+ public:
+  explicit IfstreamInputStream(const std::string& file_name)
+      : ifs_(file_name.c_str(), std::ios::in | std::ios::binary) {}
+  ~IfstreamInputStream() { ifs_.close(); }
+
+  int Read(void* buffer, int size) {
+    if (!ifs_) {
+      return -1;
+    }
+    ifs_.read(static_cast<char*>(buffer), size);
+    return (int)ifs_.gcount();
+  }
+
+ private:
+  std::ifstream ifs_;
+};
+}  // namespace
+
+@interface RunModelViewController ()
+@end
+
+@implementation RunModelViewController {
+}
+
+- (IBAction)getUrl:(id)sender {
+  NSString* inference_result = RunInferenceOnImage();
+  self.urlContentTextView.text = inference_result;
+}
+
+@end
+
+// Returns the top N confidence values over threshold in the provided vector,
+// sorted by confidence in descending order.
+static void GetTopN(
+    const Eigen::TensorMap<Eigen::Tensor<float, 1, Eigen::RowMajor>,
+                           Eigen::Aligned>& prediction,
+    const int num_results, const float threshold,
+    std::vector<std::pair<float, int> >* top_results) {
+  // Will contain top N results in ascending order.
+  std::priority_queue<std::pair<float, int>,
+      std::vector<std::pair<float, int> >,
+      std::greater<std::pair<float, int> > > top_result_pq;
+
+  const long count = prediction.size();
+  for (int i = 0; i < count; ++i) {
+    const float value = prediction(i);
+
+    // Only add it if it beats the threshold and has a chance at being in
+    // the top N.
+    if (value < threshold) {
+      continue;
+    }
+
+    top_result_pq.push(std::pair<float, int>(value, i));
+
+    // If at capacity, kick the smallest value out.
+    if (top_result_pq.size() > num_results) {
+      top_result_pq.pop();
+    }
+  }
+
+  // Copy to output vector and reverse into descending order.
+  while (!top_result_pq.empty()) {
+    top_results->push_back(top_result_pq.top());
+    top_result_pq.pop();
+  }
+  std::reverse(top_results->begin(), top_results->end());
+}
+
+
+bool PortableReadFileToProto(const std::string& file_name,
+                             ::google::protobuf::MessageLite* proto) {
+  ::google::protobuf::io::CopyingInputStreamAdaptor stream(
+      new IfstreamInputStream(file_name));
+  stream.SetOwnsCopyingStream(true);
+  // TODO(jiayq): the following coded stream is for debugging purposes to allow
+  // one to parse arbitrarily large messages for MessageLite. One most likely
+  // doesn't want to put protobufs larger than 64MB on Android, so we should
+  // eventually remove this and quit loud when a large protobuf is passed in.
+  ::google::protobuf::io::CodedInputStream coded_stream(&stream);
+  // Total bytes hard limit / warning limit are set to 1GB and 512MB
+  // respectively.
+  coded_stream.SetTotalBytesLimit(1024LL << 20, 512LL << 20);
+  return proto->ParseFromCodedStream(&coded_stream);
+}
+
+NSString* FilePathForResourceName(NSString* name, NSString* extension) {
+  NSString* file_path = [[NSBundle mainBundle] pathForResource:name ofType:extension];
+  if (file_path == NULL) {
+    LOG(FATAL) << "Couldn't find '" << [name UTF8String] << "."
+	       << [extension UTF8String] << "' in bundle.";
+  }
+  return file_path;
+}
+
+NSString* RunInferenceOnImage() {
+  tensorflow::SessionOptions options;
+
+  tensorflow::Session* session_pointer = nullptr;
+  tensorflow::Status session_status = tensorflow::NewSession(options, &session_pointer);
+  if (!session_status.ok()) {
+    std::string status_string = session_status.ToString();
+    return [NSString stringWithFormat: @"Session create failed - %s",
+	status_string.c_str()];
+  }
+  std::unique_ptr<tensorflow::Session> session(session_pointer);
+  LOG(INFO) << "Session created.";
+
+  tensorflow::GraphDef tensorflow_graph;
+  LOG(INFO) << "Graph created.";
+
+  NSString* network_path = FilePathForResourceName(@"tensorflow_inception_graph", @"pb");
+  PortableReadFileToProto([network_path UTF8String], &tensorflow_graph);
+
+  LOG(INFO) << "Creating session.";
+  tensorflow::Status s = session->Create(tensorflow_graph);
+  if (!s.ok()) {
+    LOG(ERROR) << "Could not create TensorFlow Graph: " << s;
+    return @"";
+  }
+
+  // Read the label list
+  NSString* labels_path = FilePathForResourceName(@"imagenet_comp_graph_label_strings", @"txt");
+  std::vector<std::string> label_strings;
+  std::ifstream t;
+  t.open([labels_path UTF8String]);
+  std::string line;
+  while(t){
+    std::getline(t, line);
+    label_strings.push_back(line);
+  }
+  t.close();
+
+  // Read the Grace Hopper image.
+  NSString* image_path = FilePathForResourceName(@"grace_hopper", @"jpg");
+  int image_width;
+  int image_height;
+  int image_channels;
+  std::vector<tensorflow::uint8> image_data = LoadImageFromFile(
+	[image_path UTF8String], &image_width, &image_height, &image_channels);
+  const int wanted_width = 224;
+  const int wanted_height = 224;
+  const int wanted_channels = 3;
+  const float input_mean = 117.0f;
+  const float input_std = 1.0f;
+  assert(image_channels >= wanted_channels);
+  tensorflow::Tensor image_tensor(
+      tensorflow::DT_FLOAT,
+      tensorflow::TensorShape({
+          1, wanted_height, wanted_width, wanted_channels}));
+  auto image_tensor_mapped = image_tensor.tensor<float, 4>();
+  tensorflow::uint8* in = image_data.data();
+  // tensorflow::uint8* in_end = (in + (image_height * image_width * image_channels));
+  float* out = image_tensor_mapped.data();
+  for (int y = 0; y < wanted_height; ++y) {
+    const int in_y = (y * image_height) / wanted_height;
+    tensorflow::uint8* in_row = in + (in_y * image_width * image_channels);
+    float* out_row = out + (y * wanted_width * wanted_channels);
+    for (int x = 0; x < wanted_width; ++x) {
+      const int in_x = (x * image_width) / wanted_width;
+      tensorflow::uint8* in_pixel = in_row + (in_x * image_channels);
+      float* out_pixel = out_row + (x * wanted_channels);
+      for (int c = 0; c < wanted_channels; ++c) {
+        out_pixel[c] = (in_pixel[c] - input_mean) / input_std;
+      }
+    }
+  }
+
+  NSString* result = [network_path stringByAppendingString: @" - loaded!"];
+  result = [NSString stringWithFormat: @"%@ - %lu, %s - %dx%d", result,
+	label_strings.size(), label_strings[0].c_str(), image_width, image_height];
+
+  std::string input_layer = "input";
+  std::string output_layer = "output";
+  std::vector<tensorflow::Tensor> outputs;
+  tensorflow::Status run_status = session->Run({{input_layer, image_tensor}},
+				               {output_layer}, {}, &outputs);
+  if (!run_status.ok()) {
+    LOG(ERROR) << "Running model failed: " << run_status;
+    tensorflow::LogAllRegisteredKernels();
+    result = @"Error running model";
+    return result;
+  }
+  tensorflow::string status_string = run_status.ToString();
+  result = [NSString stringWithFormat: @"%@ - %s", result,
+	status_string.c_str()];
+
+  tensorflow::Tensor* output = &outputs[0];
+  const int kNumResults = 5;
+  const float kThreshold = 0.1f;
+  std::vector<std::pair<float, int> > top_results;
+  GetTopN(output->flat<float>(), kNumResults, kThreshold, &top_results);
+
+  std::stringstream ss;
+  ss.precision(3);
+  for (const auto& result : top_results) {
+    const float confidence = result.first;
+    const int index = result.second;
+
+    ss << index << " " << confidence << "  ";
+
+    // Write out the result as a string
+    if (index < label_strings.size()) {
+      // just for safety: theoretically, the output is under 1000 unless there
+      // is some numerical issues leading to a wrong prediction.
+      ss << label_strings[index];
+    } else {
+      ss << "Prediction: " << index;
+    }
+
+    ss << "\n";
+  }
+
+  LOG(INFO) << "Predictions: " << ss.str();
+
+  tensorflow::string predictions = ss.str();
+  result = [NSString stringWithFormat: @"%@ - %s", result,
+	predictions.c_str()];
+
+  return result;
+}
diff --git a/tensorflow/examples/ios/simple/RunModelViewController.xib b/tensorflow/examples/ios/simple/RunModelViewController.xib
new file mode 100644
index 0000000000..93f334b985
--- /dev/null
+++ b/tensorflow/examples/ios/simple/RunModelViewController.xib
@@ -0,0 +1,46 @@
+<?xml version="1.0" encoding="UTF-8" standalone="no"?>
+<document type="com.apple.InterfaceBuilder3.CocoaTouch.XIB" version="3.0" toolsVersion="9531" systemVersion="15D21" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES">
+    <dependencies>
+        <plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="9529"/>
+    </dependencies>
+    <objects>
+        <placeholder placeholderIdentifier="IBFilesOwner" id="-1" userLabel="File's Owner" customClass="RunModelViewController">
+            <connections>
+                <outlet property="urlContentTextView" destination="quY-AK-ZCn" id="YjW-BO-1Ta"/>
+                <outlet property="urlTextField" destination="hPw-q5-vh5" id="wmc-b6-2CV"/>
+                <outlet property="view" destination="1" id="iHm-Rr-4wj"/>
+            </connections>
+        </placeholder>
+        <placeholder placeholderIdentifier="IBFirstResponder" id="-2" customClass="UIResponder"/>
+        <view contentMode="scaleToFill" id="1">
+            <rect key="frame" x="0.0" y="0.0" width="320" height="568"/>
+            <autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
+            <subviews>
+                <textView clipsSubviews="YES" contentMode="scaleToFill" fixedFrame="YES" editable="NO" text="The results of running the model will appear here." selectable="NO" translatesAutoresizingMaskIntoConstraints="NO" id="quY-AK-ZCn">
+                    <rect key="frame" x="40" y="99" width="240" height="168"/>
+                    <color key="backgroundColor" white="1" alpha="1" colorSpace="calibratedWhite"/>
+                    <fontDescription key="fontDescription" type="system" pointSize="14"/>
+                    <textInputTraits key="textInputTraits" autocapitalizationType="sentences"/>
+                </textView>
+                <button opaque="NO" contentMode="scaleToFill" fixedFrame="YES" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="AAC-Bk-PCC">
+                    <rect key="frame" x="76" y="37" width="168" height="30"/>
+                    <color key="backgroundColor" white="0.33333333333333331" alpha="1" colorSpace="calibratedWhite"/>
+                    <state key="normal" title="Run Model">
+                        <color key="titleShadowColor" white="0.5" alpha="1" colorSpace="calibratedWhite"/>
+                    </state>
+                    <connections>
+                        <action selector="getUrl:" destination="-1" eventType="touchUpInside" id="mdP-nK-k9T"/>
+                    </connections>
+                </button>
+            </subviews>
+            <color key="backgroundColor" red="0.78314738357315861" green="0.79869981749999996" blue="0.56305065858222869" alpha="1" colorSpace="calibratedRGB"/>
+        </view>
+        <textField opaque="NO" clipsSubviews="YES" contentMode="scaleToFill" contentHorizontalAlignment="left" contentVerticalAlignment="center" text="http://localhost:8080" borderStyle="roundedRect" placeholder="Enter URL" minimumFontSize="17" id="hPw-q5-vh5">
+            <rect key="frame" x="0.0" y="0.0" width="280" height="30"/>
+            <autoresizingMask key="autoresizingMask" flexibleMaxX="YES" flexibleMaxY="YES"/>
+            <fontDescription key="fontDescription" type="system" pointSize="14"/>
+            <textInputTraits key="textInputTraits"/>
+            <point key="canvasLocation" x="795" y="44"/>
+        </textField>
+    </objects>
+</document>
diff --git a/tensorflow/examples/ios/simple/data/grace_hopper.jpg b/tensorflow/examples/ios/simple/data/grace_hopper.jpg
new file mode 100644
index 0000000000..d2a427810f
--- /dev/null
+++ b/tensorflow/examples/ios/simple/data/grace_hopper.jpg
diff --git a/tensorflow/examples/ios/simple/ios_image_load.h b/tensorflow/examples/ios/simple/ios_image_load.h
new file mode 100644
index 0000000000..0e0b771118
--- /dev/null
+++ b/tensorflow/examples/ios/simple/ios_image_load.h
@@ -0,0 +1,27 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#ifndef TENSORFLOW_EXAMPLES_IOS_IOS_IMAGE_LOAD_H_
+#define TENSORFLOW_EXAMPLES_IOS_IOS_IMAGE_LOAD_H_
+
+#include <vector>
+
+#include "tensorflow/core/framework/types.h"
+
+std::vector<tensorflow::uint8> LoadImageFromFile(const char* file_name,
+						 int* out_width,
+						 int* out_height,
+						 int* out_channels);
+
+#endif  // TENSORFLOW_EXAMPLES_IOS_IOS_IMAGE_LOAD_H_
diff --git a/tensorflow/examples/ios/simple/ios_image_load.mm b/tensorflow/examples/ios/simple/ios_image_load.mm
new file mode 100644
index 0000000000..64d1ea21cf
--- /dev/null
+++ b/tensorflow/examples/ios/simple/ios_image_load.mm
@@ -0,0 +1,87 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "ios_image_load.h"
+
+#include <stdlib.h>
+#include <string.h>
+#include <assert.h>
+#include <stdio.h>
+
+#import <CoreImage/CoreImage.h>
+#import <ImageIO/ImageIO.h>
+
+using tensorflow::uint8;
+
+std::vector<uint8> LoadImageFromFile(const char* file_name,
+				     int* out_width, int* out_height,
+				     int* out_channels) {
+  FILE* file_handle = fopen(file_name, "rb");
+  fseek(file_handle, 0, SEEK_END);
+  const size_t bytes_in_file = ftell(file_handle);
+  fseek(file_handle, 0, SEEK_SET);
+  std::vector<uint8> file_data(bytes_in_file);
+  fread(file_data.data(), 1, bytes_in_file, file_handle);
+  fclose(file_handle);
+  CFDataRef file_data_ref = CFDataCreateWithBytesNoCopy(NULL, file_data.data(),
+						      bytes_in_file,
+						      kCFAllocatorNull);
+  CGDataProviderRef image_provider =
+    CGDataProviderCreateWithCFData(file_data_ref);
+
+  const char* suffix = strrchr(file_name, '.');
+  if (!suffix || suffix == file_name) {
+    suffix = "";
+  }
+  CGImageRef image;
+  if (strcasecmp(suffix, ".png") == 0) {
+    image = CGImageCreateWithPNGDataProvider(image_provider, NULL, true,
+					     kCGRenderingIntentDefault);
+  } else if ((strcasecmp(suffix, ".jpg") == 0) ||
+    (strcasecmp(suffix, ".jpeg") == 0)) {
+    image = CGImageCreateWithJPEGDataProvider(image_provider, NULL, true,
+					      kCGRenderingIntentDefault);
+  } else {
+    CFRelease(image_provider);
+    CFRelease(file_data_ref);
+    fprintf(stderr, "Unknown suffix for file '%s'\n", file_name);
+    *out_width = 0;
+    *out_height = 0;
+    *out_channels = 0;
+    return std::vector<uint8>();
+  }
+
+  const int width = (int)CGImageGetWidth(image);
+  const int height = (int)CGImageGetHeight(image);
+  const int channels = 4;
+  CGColorSpaceRef color_space = CGColorSpaceCreateDeviceRGB();
+  const int bytes_per_row = (width * channels);
+  const int bytes_in_image = (bytes_per_row * height);
+  std::vector<uint8> result(bytes_in_image);
+  const int bits_per_component = 8;
+  CGContextRef context = CGBitmapContextCreate(result.data(), width, height,
+    bits_per_component, bytes_per_row, color_space,
+    kCGImageAlphaPremultipliedLast | kCGBitmapByteOrder32Big);
+  CGColorSpaceRelease(color_space);
+  CGContextDrawImage(context, CGRectMake(0, 0, width, height), image);
+  CGContextRelease(context);
+  CFRelease(image);
+  CFRelease(image_provider);
+  CFRelease(file_data_ref);
+
+  *out_width = width;
+  *out_height = height;
+  *out_channels = channels;
+  return result;
+}
diff --git a/tensorflow/examples/ios/simple/main.mm b/tensorflow/examples/ios/simple/main.mm
new file mode 100644
index 0000000000..d70550a730
--- /dev/null
+++ b/tensorflow/examples/ios/simple/main.mm
@@ -0,0 +1,22 @@
+// Copyright 2015 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <UIKit/UIKit.h>
+
+int main(int argc, char * argv[]) {
+  @autoreleasepool {
+    NSString *delegateClassName = @"AppDelegate";
+    return UIApplicationMain(argc, argv, nil, delegateClassName);
+  }
+}
diff --git a/tensorflow/examples/ios/simple/tf_simple_example.xcodeproj/project.pbxproj b/tensorflow/examples/ios/simple/tf_simple_example.xcodeproj/project.pbxproj
new file mode 100644
index 0000000000..55c06e28fb
--- /dev/null
+++ b/tensorflow/examples/ios/simple/tf_simple_example.xcodeproj/project.pbxproj
@@ -0,0 +1,404 @@
+// !$*UTF8*$!
+{
+	archiveVersion = 1;
+	classes = {
+	};
+	objectVersion = 46;
+	objects = {
+
+/* Begin PBXBuildFile section */
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+/* End PBXBuildFile section */
+
+/* Begin PBXFileReference section */
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author	A. Unique TensorFlower <gardener@tensorflow.org>	2017-06-07 10:59:18 -0700
committer	TensorFlower Gardener <gardener@tensorflow.org>	2017-06-07 11:03:49 -0700
commit	fdb8e29354ce93afa8c2335a6287a59eb37d42fc (patch)
tree	75489b1dc9b502d0cde992f3faf21fbc6ef39be5 /tensorflow/examples/ios
parent	dffea202a506d7d0f5c2fb32798aecdcb1bab32a (diff)